本研究采用文献计量学方法,总结当前土壤质量研究中最小数据集(MDS)选取的方法和指标,定量分析并指出土壤质量评价中最小数据集的热点和前沿,为中国土壤质量评价和农业绿色发展提供科学参考。通过检索1991-2022年CNKI和Web of Science...本研究采用文献计量学方法,总结当前土壤质量研究中最小数据集(MDS)选取的方法和指标,定量分析并指出土壤质量评价中最小数据集的热点和前沿,为中国土壤质量评价和农业绿色发展提供科学参考。通过检索1991-2022年CNKI和Web of Science相关文献,收集了文献中310个最小数据集进行筛选,借助CiteSpace和VOSviewer对年度发文量、国家/地区、机构、期刊进行共现分析,对关键词进行突现词和聚类分析。31年来该领域文献量逐步增加并仍处于快速发展阶段,中国是发文量最多的国家,期刊载文量最多的为《土壤通报》《生态学报》和Ecological Indicators;主要研究热点表现在“农业管理对土壤质量影响、土壤退化与修复、土壤质量对气候变化的响应与应对及最小数据集筛选方法与模型构建”等方面;前期MDS在土壤质量评价中选用较多的主要为物理、化学指标,但随着土壤健康的发展,生物学指标逐步增长。在未来一段时间内MDS发文量仍为快速增长阶段,发展中国家在全球起着重要节点作用;MDS核心指标为土壤有机质/碳(SOM/SOC)、pH、全氮、速效磷和容重;未来研究应注重在基于大数据平台构建不同尺度下静态评价与动态监测相结合的综合反映土壤功能的土壤健康质量评价框架体系,探讨气候变化背景下与土壤质量变化相对应的MDS及其指标体系,构建精准反映土壤质量变化规律的评价模型与最优最小数据集。展开更多
【目的】系统探究柴达木盆地耕地耕层土壤盐碱化水平及养分状况,优化柴达木盆地耕地耕层土壤评价因子,构建评价与诊断模型,为区域粮食安全和生态可持续发展提供科学依据。【方法】以柴达木盆地耕作层土壤为对象,基于470个土壤样品的11...【目的】系统探究柴达木盆地耕地耕层土壤盐碱化水平及养分状况,优化柴达木盆地耕地耕层土壤评价因子,构建评价与诊断模型,为区域粮食安全和生态可持续发展提供科学依据。【方法】以柴达木盆地耕作层土壤为对象,基于470个土壤样品的11项土壤指标(全盐:TS、电导率:EC、全氮:TN、全磷:TP、速效氮:AN、速效磷:AP、pH、有机质:SOM、钠离子:Na^(+)、氯离子:Cl^(-)、硫酸根离子:SO_(4)^(2-)),通过主成分分析(PCA)与Norm值构建最小数据集(Minimum data set,MDS),结合多准则妥协解排序法(VIKOR法),系统评价土壤质量指数(Soil quality index,SQI)并诊断主要障碍因子。【结果】研究区土壤呈现显著盐碱化风险(TS均值2.449 g/kg,C_(V)=53.98%)和氮磷养分限制特征(TN均值为0.916 mg/kg,TP的C_(V)为118.38%);MDS筛选出TS、TN、TP、AP、Cl^(-)和SO_(4)^(2-)等6项核心指标,可替代全数据集(Total data set,TDS)精准评价土壤质量(R^(2)=0.904);VIKOR模型显示,格尔木和大柴旦地区土壤综合障碍度最高(群体效应值S>0.46),TP与SO_(4)^(2-)是主要限制因子,德令哈土壤质量最优(SQI=0.284)。【讨论】研究揭示了盐碱化与养分失衡对干旱区土壤质量的协同制约效应,为柴达木盆地耕地定向改良提供了科学依据。展开更多
In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenario...In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.展开更多
To investigate the effects of the maximum principal stress direction(θ)and cross-section shape on the failure characteristics of sandstone,true-triaxial compression experiments were conducted using cubic samples with...To investigate the effects of the maximum principal stress direction(θ)and cross-section shape on the failure characteristics of sandstone,true-triaxial compression experiments were conducted using cubic samples with rectangular,circular,and D-shaped holes.Asθincreases from 0°to 60°in the rectangular hole,the left failure location shifts from the left corner to the left sidewall,the left corner,and then the floor,while the right failure location shifts from the right corner to the right sidewall,right roof corner,and then the roof.Furthermore,the initial failure vertical stress first decreases and then increases.In comparison,the failure severity in the rectangular hole decreases for variousθvalues as 30°>45°>60°>0°.With increasingθ,the fractal dimension(D)of rock slices first increases and then decreases.For the rectangular and D-shaped holes,whenθ=0°,30°,and 90°,D for the rectangular hole is less than that of the D-shaped hole.Whenθ=45°and 60°,D for the rectangular hole is greater than that of the D-shaped hole.Theoretical analysis indicates that the stress concentration at the rectangular and D-shaped corners is greater than the other areas.The failure location rotates with the rotation ofθ,and the failure occurs on the side with a high concentration of compressive stress,while the side with the tensile and compressive stresses remains relatively stable.Therefore,the fundamental reason for the rotation of failure location is the rotation of stress concentration,and the external influencing factor is the rotation ofθ.展开更多
Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stre...Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.展开更多
The extended Kalman filter(EKF)is extensively applied in integrated navigation systems that combine the global navigation satellite system(GNSS)and strap-down inertial navigation system(SINS).However,the performance o...The extended Kalman filter(EKF)is extensively applied in integrated navigation systems that combine the global navigation satellite system(GNSS)and strap-down inertial navigation system(SINS).However,the performance of the EKF can be severely impacted by non-Gaussian noise and measurement noise uncertainties,making it difficult to achieve optimal GNSS/INS integration.Dealing with non-Gaussian noise remains a significant challenge in filter development today.Therefore,the maximum correntropy criterion(MCC)is utilized in EKFs to manage heavytailed measurement noise.However,its capability to handle non-Gaussian process noise and unknown disturbances remains largely unexplored.In this paper,we extend correntropy from using a single kernel to a multi-kernel approach.This leads to the development of a multi-kernel maximum correntropy extended Kalman filter(MKMC-EKF),which is designed to effectively manage multivariate non-Gaussian noise and disturbances.Further,theoretical analysis,including advanced stability proofs,can enhance understanding,while hybrid approaches integrating MKMC-EKF with particle filters may improve performance in nonlinear systems.The MKMC-EKF enhances estimation accuracy using a multi-kernel bandwidth approach.As bandwidth increases,the filter’s sensitivity to non-Gaussian features decreases,and its behavior progressively approximates that of the iterated EKF.The proposed approach for enhancing positioning in navigation is validated through performance evaluations,which demonstrate its practical applications in real-world systems like GPS navigation and measuring radar targets.展开更多
The presence of circles in the network maximum flow problem increases the complexity of the preflow algorithm.This study proposes a novel two-stage preflow algorithm to address this issue.First,this study proves that ...The presence of circles in the network maximum flow problem increases the complexity of the preflow algorithm.This study proposes a novel two-stage preflow algorithm to address this issue.First,this study proves that at least one zero-flow arc must be present when the flow of the network reaches its maximum value.This result indicates that the maximum flow of the network will remain constant if a zero-flow arc within a circle is removed;therefore,the maximum flow of each network without circles can be calculated.The first stage involves identifying the zero-flow arc in the circle when the network flow reaches its maximum.The second stage aims to remove the zero-flow arc identified and modified in the first stage,thereby producing a new network without circles.The maximum flow of the original looped network can be obtained by solving the maximum flow of the newly generated acyclic network.Finally,an example is provided to demonstrate the validity and feasibility of this algorithm.This algorithm not only improves computational efficiency but also provides new perspectives and tools for solving similar network optimization problems.展开更多
The age at which a woman enters natural menopause has also been associated to death from any cause.Menopause is a natural component of aging that happens between the ages of 45 and 55,with the average menopausal age b...The age at which a woman enters natural menopause has also been associated to death from any cause.Menopause is a natural component of aging that happens between the ages of 45 and 55,with the average menopausal age being 51.Previous research has revealed the age at which women reach menopause,but there is no evidence to support the link between menopause and longevity.We made a study in assessing the limits of maximum lifespan at menopausal age in our previous article.In this paper,we aim to predict the maximum lifespan of women at mean menopausal age.展开更多
Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the spe...Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the special case where p and n are comparable,we consider a much more general case in which log n=o(p^(1/3)).We prove that the maximum interpoint distance Mn=max{|X_(i)-X_(j)|;1≤i<j≤n}converges to an extreme-value distribution,where X_(i)and X_(j)denote the i-th and j-th row of M_(n,p),respectively.The proofs are completed by using the Chen-Stein Poisson approximation method and the moderation deviation principle.展开更多
Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a netwo...Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a network, the delay is with epistemic uncertainty, which makes the traditional routing scheme based on deterministic theory or probability theory not applicable. Motivated by this problem, the MCN with epistemic uncertainty is first summarized as a dynamic uncertain network based on uncertainty theory, which is widely applied to model epistemic uncertainties. Then by modeling the uncertain end-toend delay, a new delay bounded routing scheme is proposed to find the path with the maximum belief degree that satisfies the delay threshold for the dynamic uncertain network. Finally, a lowEarth-orbit satellite communication network(LEO-SCN) is used as a case to verify the effectiveness of our routing scheme. It is first modeled as a dynamic uncertain network, and then the delay bounded paths with the maximum belief degree are computed and compared under different delay thresholds.展开更多
Research on changes in the redox conditions of bottom waters is essential for understanding deep water circulation,global ocean currents,climate change,and ecosystem health.Through sedimentary geological methods,a dee...Research on changes in the redox conditions of bottom waters is essential for understanding deep water circulation,global ocean currents,climate change,and ecosystem health.Through sedimentary geological methods,a deeper understanding of the complex relationships between various environmental changes can be achieved,providing detailed evidence and theoretical support for global climate change research.The Ross Sea in Antarctica plays a key role in the formation of Antarctic bottom water(AABW),and the complex climate changes since the last glacial maximum(LGM)make it particularly significant for study.This research analyzes core ANT32-RB16C from the Ross Sea using geochemical proxies such as major and trace elements,grain size,and redox-sensitive indicators like Mn/Ti,Co/Ti,Mo/Ti,Cd/Ti,U/Th,and Ni/Co molar concentration ratios.Combining this data with a previously established chronological framework,the study explores the evolution of redox conditions in the Ross Sea’s deep waters since the LGM.The results show that the deep waters have remained oxygen-rich since the LGM,with significant changes in four stages.Stage 1(24.7–15.7 cal ka BP):Strong oxidizing conditions,likely due to enhanced formation of Ross Sea bottom water(RSBW),increasing oxygen levels.Stage 2(15.7–4.5 cal ka BP):Weakened oxidizing conditions as temperatures rose and ice shelves retreated,increasing primary productivity and depleting oxygen.Stage 3(4.5–1.5 cal ka BP):Continued decline in oxidizing conditions,possibly linked to high primary productivity and oxygen consumption.Stage 4(1.5 cal ka BP to present):A rapid recovery of oxidizing conditions,likely driven by temperature drops,increased RSBW formation,and decreased productivity.展开更多
The turbidity maximum zone(TMZ)is a distinctive aquatic environment marked by consistently higher turbidity compared to upstream and downstream section.In the TMZ,physicochemical properties such as intense light limit...The turbidity maximum zone(TMZ)is a distinctive aquatic environment marked by consistently higher turbidity compared to upstream and downstream section.In the TMZ,physicochemical properties such as intense light limitation,abundant nutrients,and rapid salinity shifts play a crucial role in shaping phytoplankton dynamics.The Qiantang River estuary-Hangzhou Bay(QRE-HZB)is a macrotidal estuary system known for its exceptionally high suspended solids concentration.To investigate the impact of TMZ on the standing crop and size structure of phytoplankton in the QRE-HZB,we conducted three cruises in dry,wet,and dry-to-wet transition seasons during 2022-2023,by assessing parameters including size fractionated chlorophyll a(chl a),turbidity,Secchi depth,temperature,salinity,nutrients,and mesozooplankton.Results reveal significant variations in the TMZ and associated environmental factors in different periods,which markedly influenced the phytoplankton chl-a concentration,size structure,and cell activity(pheophytin/chl a).The chl-a concentration was high with micro-phytoplankton predominance in wet season,while nano-phytoplankton dominated in dry season.Within the TMZ,lower chl-a concentrations and pico-chl-a contributions,alongside higher pheophytin/chl-a and micro-chl-a contributions,were observed.The Spearman’s rank correlation and generalized additive model analyses indicated strong correlations of chl-a concentrations with turbidity,nutrients,and mesozooplankton.Redundancy analysis further revealed that salinity,nutrients,and turbidity significantly regulated variations in size structure.Phytoplankton mortality within the TMZ was primarily driven by high turbidity and salinity fluctuations,reflecting the vigorous resuspension and mixing of freshwater and seawater in the QRE-HZB.These findings highlight that the standing crop and size structure of phytoplankton were strongly regulated by the TMZ and associated physicochemical factors in the macrotidal QRE-HZB.展开更多
Coal dust explosions are severe safety accidents in coal mine production,posing significant threats to life and property.Predicting the maximum explosion pressure(Pm)of coal dust using deep learning models can effecti...Coal dust explosions are severe safety accidents in coal mine production,posing significant threats to life and property.Predicting the maximum explosion pressure(Pm)of coal dust using deep learning models can effectively assess potential risks and provide a scientific basis for preventing coal dust explosions.In this study,a 20-L explosion sphere apparatus was used to test the maximum explosion pressure of coal dust under seven different particle sizes and ten mass concentrations(Cdust),resulting in a dataset of 70 experimental groups.Through Spearman correlation analysis and random forest feature selection methods,particle size(D_(10),D_(20),D_(50))and mass concentration(Cdust)were identified as critical feature parameters from the ten initial parameters of the coal dust samples.Based on this,a hybrid Long Short-Term Memory(LSTM)network model incorporating a Multi-Head Attention Mechanism and the Sparrow Search Algorithm(SSA)was proposed to predict the maximum explosion pressure of coal dust.The results demonstrate that the SSA-LSTM-Multi-Head Attention model excels in predicting the maximum explosion pressure of coal dust.The four evaluation metrics indicate that the model achieved a coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute percentage error(MAPE),and mean absolute error(MAE)of 0.9841,0.0030,0.0074,and 0.0049,respectively,in the training set.In the testing set,these values were 0.9743,0.0087,0.0108,and 0.0069,respectively.Compared to artificial neural networks(ANN),random forest(RF),support vector machines(SVM),particle swarm optimized-SVM(PSO-SVM)neural networks,and the traditional single-model LSTM,the SSA-LSTM-Multi-Head Attention model demonstrated superior generalization capability and prediction accuracy.The findings of this study not only advance the application of deep learning in coal dust explosion prediction but also provide robust technical support for the prevention and risk assessment of coal dust explosions.展开更多
Weighted exponential distribution W ED(α,λ)with shape parameterαand scale parameterλpossesses some good properties and can be used as a good fit to survival time data compared to other distributions such as gamma,...Weighted exponential distribution W ED(α,λ)with shape parameterαand scale parameterλpossesses some good properties and can be used as a good fit to survival time data compared to other distributions such as gamma,Weibull,or generalized exponential distribution.In this article,we proved the existence and uniqueness of the maximum likelihood estimator(MLE)of the parameters of W ED(α,λ)in simple random sampling(SRS)and provided explicit expressions for the Fisher information number in SRS.Moreover,we also proved the existence and uniqueness of the MLE of the parameters of W ED(α,λ)in ranked set sampling(RSS)and provided explicit expressions for the Fisher information number in RSS.Simulation studies show that these MLEs in RSS can be real competitors for those in SRS.展开更多
This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between th...This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between the NCEP Climate Forecast System version 2(CFSv2) and a high-resolution Weather Research and Forecasting(WRF) model,using gridded Tmax observation data and ERA5 reanalysis data as benchmarks. The WRF model is driven by CFSv2 multi-member ensemble hindcast and forecast data. Results indicate that the WRF model improves Tmax prediction across China, with particularly significant enhancement over the southern region of the middle and lower reaches of the Yangtze River, although a systematic cold bias remains. By applying bias correction to the daily Tmax simulations from both models, we find that the corrected WRF predictions exhibit marked improvement for both the annual and extended-range Tmax. Furthermore, this study explores the physical mechanisms contributing to the improved predictability in the regional model. The WRF model, with its refined physical parameterization schemes, better simulates middle to lower tropospheric geopotential height fields, as well as surface sensible and latent heat fluxes. These results demonstrate that the dynamical downscaling approach can significantly improve the temperature prediction in southern China, highlighting the potential applicational value of this method for extended-range high-temperature forecasting.展开更多
S100 proteins govern cellular proliferation,differentiation,apoptosis,calcium homeostasis,energy metabolism,and inflammation.This heterodimeric calcium-binding protein,consisting of the S100A8 and S100A9 subunits,modu...S100 proteins govern cellular proliferation,differentiation,apoptosis,calcium homeostasis,energy metabolism,and inflammation.This heterodimeric calcium-binding protein,consisting of the S100A8 and S100A9 subunits,modulates myeloid cell development.展开更多
文摘本研究采用文献计量学方法,总结当前土壤质量研究中最小数据集(MDS)选取的方法和指标,定量分析并指出土壤质量评价中最小数据集的热点和前沿,为中国土壤质量评价和农业绿色发展提供科学参考。通过检索1991-2022年CNKI和Web of Science相关文献,收集了文献中310个最小数据集进行筛选,借助CiteSpace和VOSviewer对年度发文量、国家/地区、机构、期刊进行共现分析,对关键词进行突现词和聚类分析。31年来该领域文献量逐步增加并仍处于快速发展阶段,中国是发文量最多的国家,期刊载文量最多的为《土壤通报》《生态学报》和Ecological Indicators;主要研究热点表现在“农业管理对土壤质量影响、土壤退化与修复、土壤质量对气候变化的响应与应对及最小数据集筛选方法与模型构建”等方面;前期MDS在土壤质量评价中选用较多的主要为物理、化学指标,但随着土壤健康的发展,生物学指标逐步增长。在未来一段时间内MDS发文量仍为快速增长阶段,发展中国家在全球起着重要节点作用;MDS核心指标为土壤有机质/碳(SOM/SOC)、pH、全氮、速效磷和容重;未来研究应注重在基于大数据平台构建不同尺度下静态评价与动态监测相结合的综合反映土壤功能的土壤健康质量评价框架体系,探讨气候变化背景下与土壤质量变化相对应的MDS及其指标体系,构建精准反映土壤质量变化规律的评价模型与最优最小数据集。
文摘【目的】系统探究柴达木盆地耕地耕层土壤盐碱化水平及养分状况,优化柴达木盆地耕地耕层土壤评价因子,构建评价与诊断模型,为区域粮食安全和生态可持续发展提供科学依据。【方法】以柴达木盆地耕作层土壤为对象,基于470个土壤样品的11项土壤指标(全盐:TS、电导率:EC、全氮:TN、全磷:TP、速效氮:AN、速效磷:AP、pH、有机质:SOM、钠离子:Na^(+)、氯离子:Cl^(-)、硫酸根离子:SO_(4)^(2-)),通过主成分分析(PCA)与Norm值构建最小数据集(Minimum data set,MDS),结合多准则妥协解排序法(VIKOR法),系统评价土壤质量指数(Soil quality index,SQI)并诊断主要障碍因子。【结果】研究区土壤呈现显著盐碱化风险(TS均值2.449 g/kg,C_(V)=53.98%)和氮磷养分限制特征(TN均值为0.916 mg/kg,TP的C_(V)为118.38%);MDS筛选出TS、TN、TP、AP、Cl^(-)和SO_(4)^(2-)等6项核心指标,可替代全数据集(Total data set,TDS)精准评价土壤质量(R^(2)=0.904);VIKOR模型显示,格尔木和大柴旦地区土壤综合障碍度最高(群体效应值S>0.46),TP与SO_(4)^(2-)是主要限制因子,德令哈土壤质量最优(SQI=0.284)。【讨论】研究揭示了盐碱化与养分失衡对干旱区土壤质量的协同制约效应,为柴达木盆地耕地定向改良提供了科学依据。
基金supported by the National Science and Technology Council,Taiwan under grants NSTC 111-2221-E-019-047 and NSTC 112-2221-E-019-030.
文摘In this paper,an advanced satellite navigation filter design,referred to as the Variational Bayesian Maximum Correntropy Extended Kalman Filter(VBMCEKF),is introduced to enhance robustness and adaptability in scenarios with non-Gaussian noise and heavy-tailed outliers.The proposed design modifies the extended Kalman filter(EKF)for the global navigation satellite system(GNSS),integrating the maximum correntropy criterion(MCC)and the variational Bayesian(VB)method.This adaptive algorithm effectively reduces non-line-of-sight(NLOS)reception contamination and improves estimation accuracy,particularly in time-varying GNSS measurements.Experimental results show that the proposed method significantly outperforms conventional approaches in estimation accuracy under heavy-tailed outliers and non-Gaussian noise.By combining MCC with VB approximation for real-time noise covariance estimation using fixed-point iteration,the VBMCEKF achieves superior filtering performance in challenging GNSS conditions.The method’s adaptability and precision make it ideal for improving satellite navigation performance in stochastic environments.
基金supported by the National Natural Science Foundation of China (Grant Nos.52304227 and 52104133)Scientific and Technological Research Platform for Disaster Prevention and Control of Deep Coal Mining (Anhui University of Science and Technology) (Grant No.DPDCM2208).
文摘To investigate the effects of the maximum principal stress direction(θ)and cross-section shape on the failure characteristics of sandstone,true-triaxial compression experiments were conducted using cubic samples with rectangular,circular,and D-shaped holes.Asθincreases from 0°to 60°in the rectangular hole,the left failure location shifts from the left corner to the left sidewall,the left corner,and then the floor,while the right failure location shifts from the right corner to the right sidewall,right roof corner,and then the roof.Furthermore,the initial failure vertical stress first decreases and then increases.In comparison,the failure severity in the rectangular hole decreases for variousθvalues as 30°>45°>60°>0°.With increasingθ,the fractal dimension(D)of rock slices first increases and then decreases.For the rectangular and D-shaped holes,whenθ=0°,30°,and 90°,D for the rectangular hole is less than that of the D-shaped hole.Whenθ=45°and 60°,D for the rectangular hole is greater than that of the D-shaped hole.Theoretical analysis indicates that the stress concentration at the rectangular and D-shaped corners is greater than the other areas.The failure location rotates with the rotation ofθ,and the failure occurs on the side with a high concentration of compressive stress,while the side with the tensile and compressive stresses remains relatively stable.Therefore,the fundamental reason for the rotation of failure location is the rotation of stress concentration,and the external influencing factor is the rotation ofθ.
基金financially supported by the National Natural Science Foundation of China(No.52204084)the Open Research Fund of the State Key Laboratory of Coal Resources and safe Mining,CUMT,China(No.SKLCRSM 23KF004)+3 种基金the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities),China(No.FRF-IDRY-GD22-002)the Fundamental Research Funds for the Central Universities and the Youth Teacher International Exchange and Growth Program,China(No.QNXM20220009)the National Key R&D Program of China(Nos.2022YFC2905600 and 2022 YFC3004601)the Science,Technology&Innovation Project of Xiongan New Area,China(No.2023XAGG0061)。
文摘Understanding the mechanical properties of the lithologies is crucial to accurately determine the horizontal stress magnitude.To investigate the correlation between the rock mass properties and maximum horizontal stress,the three-dimensional(3D)stress tensors at 89 measuring points determined using an improved overcoring technique in nine mines in China were adopted,a newly defined characteristic parameter C_(ERP)was proposed as an indicator for evaluating the structural properties of rock masses,and a fuzzy relation matrix was established using the information distribution method.The results indicate that both the vertical stress and horizontal stress exhibit a good linear growth relationship with depth.There is no remarkable correlation between the elastic modulus,Poisson's ratio and depth,and the distribution of data points is scattered and messy.Moreover,there is no obvious relationship between the rock quality designation(RQD)and depth.The maximum horizontal stress σ_(H) is a function of rock properties,showing a certain linear relationship with the C_(ERP)at the same depth.In addition,the overall change trend of σ_(H) determined by the established fuzzy identification method is to increase with the increase of C_(ERP).The fuzzy identification method also demonstrates a relatively detailed local relationship betweenσ_H and C_(ERP),and the predicted curve rises in a fluctuating way,which is in accord well with the measured stress data.
基金the support from National Science and Technology Council,Taiwan under grant numbers NSTC 113-2811-E-019-001 and NSTC 113-2221-E-019-059.
文摘The extended Kalman filter(EKF)is extensively applied in integrated navigation systems that combine the global navigation satellite system(GNSS)and strap-down inertial navigation system(SINS).However,the performance of the EKF can be severely impacted by non-Gaussian noise and measurement noise uncertainties,making it difficult to achieve optimal GNSS/INS integration.Dealing with non-Gaussian noise remains a significant challenge in filter development today.Therefore,the maximum correntropy criterion(MCC)is utilized in EKFs to manage heavytailed measurement noise.However,its capability to handle non-Gaussian process noise and unknown disturbances remains largely unexplored.In this paper,we extend correntropy from using a single kernel to a multi-kernel approach.This leads to the development of a multi-kernel maximum correntropy extended Kalman filter(MKMC-EKF),which is designed to effectively manage multivariate non-Gaussian noise and disturbances.Further,theoretical analysis,including advanced stability proofs,can enhance understanding,while hybrid approaches integrating MKMC-EKF with particle filters may improve performance in nonlinear systems.The MKMC-EKF enhances estimation accuracy using a multi-kernel bandwidth approach.As bandwidth increases,the filter’s sensitivity to non-Gaussian features decreases,and its behavior progressively approximates that of the iterated EKF.The proposed approach for enhancing positioning in navigation is validated through performance evaluations,which demonstrate its practical applications in real-world systems like GPS navigation and measuring radar targets.
基金The National Natural Science Foundation of China(No.72001107,72271120)the Fundamental Research Funds for the Central Universities(No.NS2024047,NP2024106)the China Postdoctoral Science Foundation(No.2020T130297,2019M660119).
文摘The presence of circles in the network maximum flow problem increases the complexity of the preflow algorithm.This study proposes a novel two-stage preflow algorithm to address this issue.First,this study proves that at least one zero-flow arc must be present when the flow of the network reaches its maximum value.This result indicates that the maximum flow of the network will remain constant if a zero-flow arc within a circle is removed;therefore,the maximum flow of each network without circles can be calculated.The first stage involves identifying the zero-flow arc in the circle when the network flow reaches its maximum.The second stage aims to remove the zero-flow arc identified and modified in the first stage,thereby producing a new network without circles.The maximum flow of the original looped network can be obtained by solving the maximum flow of the newly generated acyclic network.Finally,an example is provided to demonstrate the validity and feasibility of this algorithm.This algorithm not only improves computational efficiency but also provides new perspectives and tools for solving similar network optimization problems.
文摘The age at which a woman enters natural menopause has also been associated to death from any cause.Menopause is a natural component of aging that happens between the ages of 45 and 55,with the average menopausal age being 51.Previous research has revealed the age at which women reach menopause,but there is no evidence to support the link between menopause and longevity.We made a study in assessing the limits of maximum lifespan at menopausal age in our previous article.In this paper,we aim to predict the maximum lifespan of women at mean menopausal age.
基金Supported by the National Natural Science Foundation of China(Grant Nos.1177117812171198)+2 种基金the Science and Technology Development Program of Jilin Province(Grant No.20210101467JC)the Technology Program of Jilin Educational Department During the“14th Five-Year”Plan Period(Grant No.JJKH20241239KJ)the Fundamental Research Funds for the Central Universities.
文摘Let M_(n,p)=(X_(i,k))_(n×p)be an n×p random matrix whose p columns X^((1)),...,X^((p))are an n-dimensional i.i.d.random sample of size p from 1-dependent Gaussian populations.Instead of investigating the special case where p and n are comparable,we consider a much more general case in which log n=o(p^(1/3)).We prove that the maximum interpoint distance Mn=max{|X_(i)-X_(j)|;1≤i<j≤n}converges to an extreme-value distribution,where X_(i)and X_(j)denote the i-th and j-th row of M_(n,p),respectively.The proofs are completed by using the Chen-Stein Poisson approximation method and the moderation deviation principle.
基金National Natural Science Foundation of China (61773044,62073009)National key Laboratory of Science and Technology on Reliability and Environmental Engineering(WDZC2019601A301)。
文摘Delay aware routing is now widely used to provide efficient network transmission. However, for newly developing or developed mobile communication networks(MCN), only limited delay data can be obtained. In such a network, the delay is with epistemic uncertainty, which makes the traditional routing scheme based on deterministic theory or probability theory not applicable. Motivated by this problem, the MCN with epistemic uncertainty is first summarized as a dynamic uncertain network based on uncertainty theory, which is widely applied to model epistemic uncertainties. Then by modeling the uncertain end-toend delay, a new delay bounded routing scheme is proposed to find the path with the maximum belief degree that satisfies the delay threshold for the dynamic uncertain network. Finally, a lowEarth-orbit satellite communication network(LEO-SCN) is used as a case to verify the effectiveness of our routing scheme. It is first modeled as a dynamic uncertain network, and then the delay bounded paths with the maximum belief degree are computed and compared under different delay thresholds.
基金The National Key R&D Program of China under contract No. 2023YFC28 11305the Scientific Research Fund of the Second Institute of Oceanography,MNR under contract No. SZ2405the Impact and Response of Antarctic Seas to Climate Change under contract No. IRASCC
文摘Research on changes in the redox conditions of bottom waters is essential for understanding deep water circulation,global ocean currents,climate change,and ecosystem health.Through sedimentary geological methods,a deeper understanding of the complex relationships between various environmental changes can be achieved,providing detailed evidence and theoretical support for global climate change research.The Ross Sea in Antarctica plays a key role in the formation of Antarctic bottom water(AABW),and the complex climate changes since the last glacial maximum(LGM)make it particularly significant for study.This research analyzes core ANT32-RB16C from the Ross Sea using geochemical proxies such as major and trace elements,grain size,and redox-sensitive indicators like Mn/Ti,Co/Ti,Mo/Ti,Cd/Ti,U/Th,and Ni/Co molar concentration ratios.Combining this data with a previously established chronological framework,the study explores the evolution of redox conditions in the Ross Sea’s deep waters since the LGM.The results show that the deep waters have remained oxygen-rich since the LGM,with significant changes in four stages.Stage 1(24.7–15.7 cal ka BP):Strong oxidizing conditions,likely due to enhanced formation of Ross Sea bottom water(RSBW),increasing oxygen levels.Stage 2(15.7–4.5 cal ka BP):Weakened oxidizing conditions as temperatures rose and ice shelves retreated,increasing primary productivity and depleting oxygen.Stage 3(4.5–1.5 cal ka BP):Continued decline in oxidizing conditions,possibly linked to high primary productivity and oxygen consumption.Stage 4(1.5 cal ka BP to present):A rapid recovery of oxidizing conditions,likely driven by temperature drops,increased RSBW formation,and decreased productivity.
基金Supported by the National Key Research and Development Program of China(No.2021 YFC 3101702)the Key R&D Program of Zhejiang(No.2022 C 03044)+2 种基金the Scientific Research Fund of the Second Institute of Oceanography,MNR(No.JG 1521)the Project of State Key Laboratory of Satellite Ocean Environment Dynamics,Second Institute of Oceanography(No.SOEDZZ 2202)the National Program on Global Change and Air-Sea Interaction(Phase Ⅱ)-Hypoxia and Acidification Monitoring and Warning Project in the Changjiang River estuary,and Long-term Observation and Research Plan in the Changjiang River estuary and Adjacent East China Sea(LORCE)Project(No.SZ 2001)。
文摘The turbidity maximum zone(TMZ)is a distinctive aquatic environment marked by consistently higher turbidity compared to upstream and downstream section.In the TMZ,physicochemical properties such as intense light limitation,abundant nutrients,and rapid salinity shifts play a crucial role in shaping phytoplankton dynamics.The Qiantang River estuary-Hangzhou Bay(QRE-HZB)is a macrotidal estuary system known for its exceptionally high suspended solids concentration.To investigate the impact of TMZ on the standing crop and size structure of phytoplankton in the QRE-HZB,we conducted three cruises in dry,wet,and dry-to-wet transition seasons during 2022-2023,by assessing parameters including size fractionated chlorophyll a(chl a),turbidity,Secchi depth,temperature,salinity,nutrients,and mesozooplankton.Results reveal significant variations in the TMZ and associated environmental factors in different periods,which markedly influenced the phytoplankton chl-a concentration,size structure,and cell activity(pheophytin/chl a).The chl-a concentration was high with micro-phytoplankton predominance in wet season,while nano-phytoplankton dominated in dry season.Within the TMZ,lower chl-a concentrations and pico-chl-a contributions,alongside higher pheophytin/chl-a and micro-chl-a contributions,were observed.The Spearman’s rank correlation and generalized additive model analyses indicated strong correlations of chl-a concentrations with turbidity,nutrients,and mesozooplankton.Redundancy analysis further revealed that salinity,nutrients,and turbidity significantly regulated variations in size structure.Phytoplankton mortality within the TMZ was primarily driven by high turbidity and salinity fluctuations,reflecting the vigorous resuspension and mixing of freshwater and seawater in the QRE-HZB.These findings highlight that the standing crop and size structure of phytoplankton were strongly regulated by the TMZ and associated physicochemical factors in the macrotidal QRE-HZB.
基金funded by the Research on Intelligent Mining Geological Model and Ventilation Model for Extremely Thin Coal Seam in Heilongjiang Province,China(2021ZXJ02A03)the Demonstration of Intelligent Mining for Comprehensive Mining Face in Extremely Thin Coal Seam in Heilongjiang Province,China(2021ZXJ02A04)the Natural Science Foundation of Heilongjiang Province,China(LH2024E112).
文摘Coal dust explosions are severe safety accidents in coal mine production,posing significant threats to life and property.Predicting the maximum explosion pressure(Pm)of coal dust using deep learning models can effectively assess potential risks and provide a scientific basis for preventing coal dust explosions.In this study,a 20-L explosion sphere apparatus was used to test the maximum explosion pressure of coal dust under seven different particle sizes and ten mass concentrations(Cdust),resulting in a dataset of 70 experimental groups.Through Spearman correlation analysis and random forest feature selection methods,particle size(D_(10),D_(20),D_(50))and mass concentration(Cdust)were identified as critical feature parameters from the ten initial parameters of the coal dust samples.Based on this,a hybrid Long Short-Term Memory(LSTM)network model incorporating a Multi-Head Attention Mechanism and the Sparrow Search Algorithm(SSA)was proposed to predict the maximum explosion pressure of coal dust.The results demonstrate that the SSA-LSTM-Multi-Head Attention model excels in predicting the maximum explosion pressure of coal dust.The four evaluation metrics indicate that the model achieved a coefficient of determination(R^(2)),root mean square error(RMSE),mean absolute percentage error(MAPE),and mean absolute error(MAE)of 0.9841,0.0030,0.0074,and 0.0049,respectively,in the training set.In the testing set,these values were 0.9743,0.0087,0.0108,and 0.0069,respectively.Compared to artificial neural networks(ANN),random forest(RF),support vector machines(SVM),particle swarm optimized-SVM(PSO-SVM)neural networks,and the traditional single-model LSTM,the SSA-LSTM-Multi-Head Attention model demonstrated superior generalization capability and prediction accuracy.The findings of this study not only advance the application of deep learning in coal dust explosion prediction but also provide robust technical support for the prevention and risk assessment of coal dust explosions.
基金Supported by the National Science Foundation of China(11901236,12261036)Scientific Research Fund of Hunan Provincial Education Department(21A0328)+2 种基金Provincial Natural Science Foundation of Hunan(2022JJ30469)Young Core Teacher Foundation of Hunan Province([2020]43)Provincial Postgraduate Innovation Foundation of Hunan(CX20221113)。
文摘Weighted exponential distribution W ED(α,λ)with shape parameterαand scale parameterλpossesses some good properties and can be used as a good fit to survival time data compared to other distributions such as gamma,Weibull,or generalized exponential distribution.In this article,we proved the existence and uniqueness of the maximum likelihood estimator(MLE)of the parameters of W ED(α,λ)in simple random sampling(SRS)and provided explicit expressions for the Fisher information number in SRS.Moreover,we also proved the existence and uniqueness of the MLE of the parameters of W ED(α,λ)in ranked set sampling(RSS)and provided explicit expressions for the Fisher information number in RSS.Simulation studies show that these MLEs in RSS can be real competitors for those in SRS.
基金National Natural Science Foundation of China(42275030, U2242206, 41730964)Joint Research Project for Meteorological Capacity Improvement (22NLTSZ002)+4 种基金National Key Research and Development Program (2018YFC1506006)China Meteorological Administration Project for Innovation and Development (CXFZ2022J009, CXFZ2022J031)Key Innovation Team of Climate Prediction of China Meteorological Ministration (CMA2023ZD03)Shandong Provincial Natural Science Foundation (ZR2023QD086)UK-China Research & Innovation Partnership Fund through the Met Office Climate Science for Service Partnership (CSSP) China as part of the Newton Fund。
文摘This study aims to enhance the extended-range prediction of midsummer(July) maximum temperature(Tmax)through a dynamical downscaling method. We compare the prediction skills of July Tmax over southern China between the NCEP Climate Forecast System version 2(CFSv2) and a high-resolution Weather Research and Forecasting(WRF) model,using gridded Tmax observation data and ERA5 reanalysis data as benchmarks. The WRF model is driven by CFSv2 multi-member ensemble hindcast and forecast data. Results indicate that the WRF model improves Tmax prediction across China, with particularly significant enhancement over the southern region of the middle and lower reaches of the Yangtze River, although a systematic cold bias remains. By applying bias correction to the daily Tmax simulations from both models, we find that the corrected WRF predictions exhibit marked improvement for both the annual and extended-range Tmax. Furthermore, this study explores the physical mechanisms contributing to the improved predictability in the regional model. The WRF model, with its refined physical parameterization schemes, better simulates middle to lower tropospheric geopotential height fields, as well as surface sensible and latent heat fluxes. These results demonstrate that the dynamical downscaling approach can significantly improve the temperature prediction in southern China, highlighting the potential applicational value of this method for extended-range high-temperature forecasting.
基金supported by grants from the National Natural Science Foundation of China(Grant Nos.82170160 and 32000604)the Provincial Natural Science Foundation of Hunan(Grant Nos.2021JJ30163 and 2022JJ20021)+3 种基金the Changsha Municipal Natural Science Foundation(Grant No.kq2007053)the Global Research Award from American Society of Hematology to Y.Mpartially supported by the National Natural Science Foundation of China(Grant No.82470145)Mount Taishan Scholar Young Expert of Shandong Province(Grant No.tsqn202103167)to S.X。
文摘S100 proteins govern cellular proliferation,differentiation,apoptosis,calcium homeostasis,energy metabolism,and inflammation.This heterodimeric calcium-binding protein,consisting of the S100A8 and S100A9 subunits,modulates myeloid cell development.
