The phenomenon of nutrient maximums at 70～200 m occurred only in the regionof the Canada Basin among the world oceans. The prevailing hypothesis was that the direct injectionof the low-temperature high-nutrient brine...The phenomenon of nutrient maximums at 70～200 m occurred only in the regionof the Canada Basin among the world oceans. The prevailing hypothesis was that the direct injectionof the low-temperature high-nutrient brines from the Chukchi Sea shelf (【 50 m) in winter providedthe nutrient maximums. However, we found that there are five problems in the direct injectionprocess. Formerly Jin et al. considered that the formation of nutrient maximums can be a process oflocally long-term regeneration. Here we propose a regeneration-mixture process. Data of temperature,salinity, oxygen and nutrients were collected at three stations in the southern Canada Basin duringthe summer 1999 cruise. We identified the cores of the surface, near-surface, potential temperaturemaximum waters and Arctic Bottom Water by the diagrams and vertical profiles of salinity, potentialtemperature, oxygen and nutrients. The historical ^(129)I data indicated that the surface andnear-surface waters were Pacific-origin, but the waters below the potential temperature maximum coredepth was Atlantic-origin. Along with the correlation of nutrient maximums and very low oxygencontents in the near-surface water, we hypothesize that, the putative organic matter was decomposedto inorganic nutrients; and the Pacific water was mixed with the Atlantic water in the transitionzone. The idea of the regeneration-mixture process agrees with the historical observations of noapparent seasonal changes, the smooth nutrient profiles, the lowest saturation of CaCO_3 above 400m, low rate of CFC-11 ventilation and ~3H-~3He ages of 8～18 a around the nutrient maximum depths.展开更多
Climate change is altering river regimes in mountainous regions,affecting water availability and the functioning of aquatic ecosystems.In the Andes Mountains,characterizing the natural flow regime is essential for est...Climate change is altering river regimes in mountainous regions,affecting water availability and the functioning of aquatic ecosystems.In the Andes Mountains,characterizing the natural flow regime is essential for establishing operational conditions that balance multiple water uses(irrigation,supply,hydropower)with the conservation of high-elevation ecosystems in the context of increasing hydroclimatic variability.This study analyzes extreme hydrological conditions in nivoglacial rivers of the upper Mendoza River Basin(Argentina),using indicators of magnitude,frequency,duration,and timing of high(HP)and low(LP)pulses.Daily flow records from the Cuevas,Vacas,Tupungato,and Mendoza Rivers were used to define eight ecologically relevant extreme hydrological parameters over the period 1956–2023.The results reveal a reduction in the magnitude of extreme flows since 2010(−30%to–55%)and significant delays in their timing,with maximum and minimum flow shifting by 15–20 days later in recent decades.The duration of LP events increased by 120%–240%in the Cuevas,Tupungato,and Mendoza Rivers,while in the Tupungato River,HP events tended to occur less frequently but with longer durations.These changes are associated with a 0.1℃decade^(−1)rise in mean temperature and a∼25%decrease in precipitation since 2009.Such trends have major implications for water resource management and the resilience of high-Andean ecosystems under climate warming.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
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
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
Statistical characteristics and the classification of the topside ionospheric mid-latitude trough are systemically analyzed,using observations from the Defense Meteorological Satellite Program F18(DMSP-F18)satellite.T...Statistical characteristics and the classification of the topside ionospheric mid-latitude trough are systemically analyzed,using observations from the Defense Meteorological Satellite Program F18(DMSP-F18)satellite.The data was obtained at an altitude of around 860 km in near polar orbit,throughout 2013.Our study identified the auroral boundary based on the in-situ electron density and electron spectrum,allowing us to precisely determine the location of the mid-latitude trough.This differs from most previous works,which only use Total Electron Content(TEC)or in-situ electron density.In our study,the troughs exhibited a higher occurrence rate in local winter than in summer,and extended to lower latitudes with increasing geomagnetic activity.It was found that the ionospheric mid-latitude trough,which is associated with temperature changes or enhanced ion drift,exhibited distinct characteristics.Specifically,the ionospheric mid-latitude troughs related to electron temperature(Te)peak were located more equatorward of auroral oval boundary in winter than in summer.The ionospheric mid-latitude troughs related to Te-maximum were less frequently observed at 60−70°S magnetic latitude and 90−240°E longitude.Furthermore,the troughs related to ion temperature(Ti)maximums were observed at relatively higher latitudes,occurring more frequently in winter.In addition,the troughs related to ion velocity(Vi)maximums could be observed in all seasons.The troughs with the maximum-Ti and maximum-Vi were located closer to the equatorward boundary of the auroral oval at the nightside,and in both hemispheres.This implies that enhanced ion drift velocity contributes to increased collisional frictional heating and enhanced ion temperatures,resulting in a density depletion within the trough region.展开更多
Let(M,g)be a compact Riemann surface with unit area,h a smooth function on M.The Kazdan-Warner problem is that under what kind of conditions on h the equationΔu=8π-8πhe^(u) has a solution.In this survey article,we ...Let(M,g)be a compact Riemann surface with unit area,h a smooth function on M.The Kazdan-Warner problem is that under what kind of conditions on h the equationΔu=8π-8πhe^(u) has a solution.In this survey article,we shall review the development of this problem along the variational method.展开更多
Gamma-ray imaging systems are powerful tools in radiographic diagnosis.However,the recorded images suffer from degradations such as noise,blurring,and downsampling,consequently failing to meet high-precision diagnosti...Gamma-ray imaging systems are powerful tools in radiographic diagnosis.However,the recorded images suffer from degradations such as noise,blurring,and downsampling,consequently failing to meet high-precision diagnostic requirements.In this paper,we propose a novel single-image super-resolution algorithm to enhance the spatial resolution of gamma-ray imaging systems.A mathematical model of the gamma-ray imaging system is established based on maximum a posteriori estimation.Within the plug-and-play framework,the half-quadratic splitting method is employed to decouple the data fidelit term and the regularization term.An image denoiser using convolutional neural networks is adopted as an implicit image prior,referred to as a deep denoiser prior,eliminating the need to explicitly design a regularization term.Furthermore,the impact of the image boundary condition on reconstruction results is considered,and a method for estimating image boundaries is introduced.The results show that the proposed algorithm can effectively addresses boundary artifacts.By increasing the pixel number of the reconstructed images,the proposed algorithm is capable of recovering more details.Notably,in both simulation and real experiments,the proposed algorithm is demonstrated to achieve subpixel resolution,surpassing the Nyquist sampling limit determined by the camera pixel size.展开更多
The southern region of Saudi Arabia exhibits a distinct seismic profile shaped by the Red Sea Rift and local fault systems, necessitating rigorous seismic hazard evaluations and tailored structural design strategies. ...The southern region of Saudi Arabia exhibits a distinct seismic profile shaped by the Red Sea Rift and local fault systems, necessitating rigorous seismic hazard evaluations and tailored structural design strategies. This study applies a robust Probabilistic Seismic Hazard Analysis (PSHA) framework to compute Maximum Considered Earthquake (MCE) and Risk-Targeted Maximum Considered Earthquake (MCER) values for major cities, including Jazan, Abha, and Najran. Utilizing local seismotectonic models, ground motion prediction equations (GMPEs), and soil classifications, the study generates precise ground motion parameters critical for infrastructure planning and safety. Results indicate significant seismic hazard variability, with Jazan showing high seismic risks with an MCER SA (0.2 s) of 0.45 g, compared to Najran’s lower risks at 0.23 g. Structural design guidelines, informed by MCE and MCER calculations, prioritize the integration of site-specific seismic data, enhanced ductility requirements, and advanced analytical methods to ensure resilient and sustainable infrastructure. The study underscores the necessity of localized seismic assessments and modern engineering practices to effectively mitigate seismic risks in this geologically complex region.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 rapid expansion of tobacco farming poses a significant threat to biodiversity in Yunnan Province,China,a region known for its rich biodiversity.This study aims to understand the trade-offs between tobacco farming ...The rapid expansion of tobacco farming poses a significant threat to biodiversity in Yunnan Province,China,a region known for its rich biodiversity.This study aims to understand the trade-offs between tobacco farming and higher plant species diversity,and to identify priority counties for conservation.We employed an integrated approach combining species distribution modeling,GIS overlay analysis,and empirical spatial regression to em pirically assess the impact of tobacco farming intensity on biodiversity risk.Our findings reveal a compelling negative spatial correlation between tobacco farming expansion and higher plant species diversity.Specifically,southern counties in Wenshan and Honghe prefectures are major priority areas of conservation that exhibit signif icant spatial correlations between biodiversity risks and high tobacco farming intensity.Quantitatively,at county level,a 1%increase in tobacco farming area corresponds to a 0.094%decrease in endemic higher plant species richness across the entire province.These results underscore the need for targeted and region-specific regulations to mitigate biodiversity loss and promote sustainable development in Yunnan Province.The integrated approach used in this study provides a comprehensive assessment of the tobacco-biodiversity trade-offs,offering actionable insights for policymaking.展开更多
During upward horizontal stratified backfill mining,stable backfill is essential for cap and sill pillar recovery.Currently,the primary method for calculating the required strength of backfill is the generalized three...During upward horizontal stratified backfill mining,stable backfill is essential for cap and sill pillar recovery.Currently,the primary method for calculating the required strength of backfill is the generalized three-dimensional(3 D)vertical stress model,which ignores the effect of mine depth,failing to obtain the vertical stress at different positions along stope length.Therefore,this paper develops and validates an improved 3 D model solution through numerical simulation in Rhino-FLAC^(3D),and examines the stress state and stability of backfill under different conditions.The results show that the improved model can accurately calculate the vertical stress at different mine depths and positions along stope length.The error rates between the results of the improved model and numerical simulation are below 4%,indicating high reliability and applicability.The maximum vertical stress(σ_(zz,max))in backfill is positively correlated with the degree of rock-backfill closure,which is enhanced by mine depth and elastic modulus of backfill,while weakened by stope width and inclination,backfill friction angle,and elastic modulus of rock mass.Theσ_(zz,max)reaches its peak when the stope length is 150 m,whileσ_(zz,max)is insensitive to changes in rock-backfill interface parameters.In all cases,the backfill stability can be improved by reducingσ_(zz,max).The results provide theoretical guidance for the backfill strength design and the safe and efficient recovery of ore pillars in deep mining.展开更多
Amid increasingly frequent military conflicts and explosion events,accurately predicting the dynamic response of reinforced concrete(RC) slabs,key load-bearing components in building structures,is essential for unders...Amid increasingly frequent military conflicts and explosion events,accurately predicting the dynamic response of reinforced concrete(RC) slabs,key load-bearing components in building structures,is essential for understanding blast-induced damage and enhancing structural protection.However,current approaches predominantly rely on experimental tests,finite element(FE) simulations,and conventional machine learning(ML) techniques,which are o ften costly,inefficie nt,narrowly applicable,and insufficiently accurate.To overcome these challenges,this study aims to optimize ML models,refine architectural designs,and improve model interpretability.A comprehensive dataset comprising 489 samples was constructed by integrating experimental and simulation data from existing literature,incorporating 15 input features and one target variable.Based on this dataset,a novel method,termed MOPSO-TXGBoost,was proposed.Building on XGBoost as a baseline,the method employs multiobjective particle swarm optimization(MOPSO) for hyperparameter tuning,introduces a tri-stream stacking architecture to enhance feature representation,and trains three distinct models to improve generalization performance.A weighted fusion strategy is employed to further enhance the accuracy of predictio n.Additio nally,a model comprehensive evaluation(MCE) index is introduced,which integrates error metrics and fitting performance to facilitate systematic model assessment.Experimental results indicate that,compared with the baseline XGBoost model,the proposed approach reduces prediction error by 61.4% and increases the coefficient of determination(R^(2)) by 0.217.Moreover,it outperforms several mainstream machine learning(ML) algorithms.The findings of this study advance ML-based blast damage prediction and provide theoretical support for safety assessment and protection optimization of RC slab structures.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
Triggered seismicity is a key hazard where fluids are injected or withdrawn from the subsurface and may impact permeability. Understanding the mechanisms that control fluid injection-triggered seismicity allows its mi...Triggered seismicity is a key hazard where fluids are injected or withdrawn from the subsurface and may impact permeability. Understanding the mechanisms that control fluid injection-triggered seismicity allows its mitigation. Key controls on seismicity are defined in terms of fault and fracture strength, second-order frictional response and stability, and competing fluid-driven mechanisms for arrest. We desire to constrain maximum event magnitudes in triggered earthquakes by relating pre-existing critical stresses to fluid injection volume to explain why some recorded events are significantly larger than anticipated seismic moment thresholds. This formalism is consistent with several uncharacteristically large fluid injection-triggered earthquakes. Such methods of reactivating fractures and faults by hydraulic stimulation in shear or tensile fracturing are routinely used to create permeability in the subsurface. Microearthquakes (MEQs) generated by such stimulations can be used to diagnose permeability evolution. Although high-fidelity data sets are scarce, the EGS-Collab and Utah FORGE hydraulic stimulation field demonstration projects provide high-fidelity data sets that concurrently track permeability evolution and triggered seismicity. Machine learning deciphers the principal features of MEQs and the resulting permeability evolution that best track permeability changes – with transfer learning methods allowing robust predictions across multiple eological settings. Changes in permeability at reactivated fractures in both shear and extensional modes suggest that permeability change (Δk) scales with the seismic moment (M) of individual MEQs as Δk∝M. This scaling relation is exact at early times but degrades with successive MEQs, but provides a method for characterizing crustal permeability evolution using MEQs, alone. Importantly, we quantify for the first time the role of prestress in defining the elevated magnitude and seismic moment of fluid injection-triggered events, and demonstrate that such MEQs can also be used as diagnostic in quantifying permeability evolution in the crust.展开更多
Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like freq...Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like frequency from such signals is possible,achieving high-precision vibration parameters remains challenging.This paper proposed a novel two-stage off-grid estimation method.It leverages a unique array layout(coprime array)to obtain a regular augmented covariance matrix.Subsequently,parameters in the matrix are recovered using the sparse iterative covariance-based estimation method based on covariance fitting criteria.Finally,high-precision estimates of imprecise parameters are obtained using unconditional maximum likelihood estimation,effectively eliminating the effects of basis mismatch.Through substantial numerical and experimental validation,the proposed method demonstrates significantly higher accuracy compared to classical BTT parameter estimation methods,approaching the lower bound of unbiased estimation variance.Furthermore,due to its immunity to frequency gridding,it can track minor frequency deviations,making it more suitable for indicating blade condition.展开更多
Accelerated life tests play a vital role in reliability analysis,especially as advanced technologies lead to the production of highly reliable products to meet market demands and competition.Among these tests,progress...Accelerated life tests play a vital role in reliability analysis,especially as advanced technologies lead to the production of highly reliable products to meet market demands and competition.Among these tests,progressive-stress accelerated life tests(PSALT)allow for continuous changes in applied stress.Additionally,the generalized progressive hybrid censoring(GPHC)scheme has attracted significant attention in reliability and survival analysis,particularly for handling censored data in accelerated testing.It has been applied to various failure models,including competing risks and step-stress models.However,despite its growing relevance,a notable gap remains in the literature regarding the application of GPHC in PSALT models.This paper addresses that gap by studying PSALT under a GPHC scheme with binomial removal.Specifically,it considers lifetimes following the quasi-Xgamma distribution.Model parameters are estimated using both maximum likelihood and Bayesian methods under gamma priors.Interval estimation is provided through approximate confidence intervals,bootstrap methods,and Bayesian credible intervals.Bayesian estimators are derived under squared error and entropy loss functions,using informative priors in simulation and non-informative priors in real data applications.A simulation study is conducted to evaluate various censoring schemes,with coverage probabilities and interval widths assessed via Monte Carlo simulations.Additionally,Bayesian predictive estimates and intervals are presented.The proposed methodology is illustrated through the analysis of two real-world accelerated life test datasets.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
基金supported by the Ministry of Finance of China,organized by the Chinese Arctic and Antarctic Administration(CAA)supported by the National Natu-ral Science Foundation of China under contract Nos 40476003 and 40403013the National“973”Pro-gram of China under contract No.G1999043704.
文摘The phenomenon of nutrient maximums at 70～200 m occurred only in the regionof the Canada Basin among the world oceans. The prevailing hypothesis was that the direct injectionof the low-temperature high-nutrient brines from the Chukchi Sea shelf (【 50 m) in winter providedthe nutrient maximums. However, we found that there are five problems in the direct injectionprocess. Formerly Jin et al. considered that the formation of nutrient maximums can be a process oflocally long-term regeneration. Here we propose a regeneration-mixture process. Data of temperature,salinity, oxygen and nutrients were collected at three stations in the southern Canada Basin duringthe summer 1999 cruise. We identified the cores of the surface, near-surface, potential temperaturemaximum waters and Arctic Bottom Water by the diagrams and vertical profiles of salinity, potentialtemperature, oxygen and nutrients. The historical ^(129)I data indicated that the surface andnear-surface waters were Pacific-origin, but the waters below the potential temperature maximum coredepth was Atlantic-origin. Along with the correlation of nutrient maximums and very low oxygencontents in the near-surface water, we hypothesize that, the putative organic matter was decomposedto inorganic nutrients; and the Pacific water was mixed with the Atlantic water in the transitionzone. The idea of the regeneration-mixture process agrees with the historical observations of noapparent seasonal changes, the smooth nutrient profiles, the lowest saturation of CaCO_3 above 400m, low rate of CFC-11 ventilation and ~3H-~3He ages of 8～18 a around the nutrient maximum depths.
基金National Scientific and Technical Research Council of Argentina(CONICET),Grant/Award Number:PIBAA2022-202328720210100485CO。
文摘Climate change is altering river regimes in mountainous regions,affecting water availability and the functioning of aquatic ecosystems.In the Andes Mountains,characterizing the natural flow regime is essential for establishing operational conditions that balance multiple water uses(irrigation,supply,hydropower)with the conservation of high-elevation ecosystems in the context of increasing hydroclimatic variability.This study analyzes extreme hydrological conditions in nivoglacial rivers of the upper Mendoza River Basin(Argentina),using indicators of magnitude,frequency,duration,and timing of high(HP)and low(LP)pulses.Daily flow records from the Cuevas,Vacas,Tupungato,and Mendoza Rivers were used to define eight ecologically relevant extreme hydrological parameters over the period 1956–2023.The results reveal a reduction in the magnitude of extreme flows since 2010(−30%to–55%)and significant delays in their timing,with maximum and minimum flow shifting by 15–20 days later in recent decades.The duration of LP events increased by 120%–240%in the Cuevas,Tupungato,and Mendoza Rivers,while in the Tupungato River,HP events tended to occur less frequently but with longer durations.These changes are associated with a 0.1℃decade^(−1)rise in mean temperature and a∼25%decrease in precipitation since 2009.Such trends have major implications for water resource management and the resilience of high-Andean ecosystems under climate warming.
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supported by the National Key R&D Program of China(2022YFF0504400)the National Natural Science Foundation of China(42188101,42274195,42174193)+2 种基金the International Partnership Program Of Chinese Academy of Sciences(Grant No.183311KYSB20200003)the USTC Research Funds of the Double First-Class Initiative(YD2080002013)the Joint Open Fund of Mengcheng National Geophysical Observatory(MENGO-202408).
文摘Statistical characteristics and the classification of the topside ionospheric mid-latitude trough are systemically analyzed,using observations from the Defense Meteorological Satellite Program F18(DMSP-F18)satellite.The data was obtained at an altitude of around 860 km in near polar orbit,throughout 2013.Our study identified the auroral boundary based on the in-situ electron density and electron spectrum,allowing us to precisely determine the location of the mid-latitude trough.This differs from most previous works,which only use Total Electron Content(TEC)or in-situ electron density.In our study,the troughs exhibited a higher occurrence rate in local winter than in summer,and extended to lower latitudes with increasing geomagnetic activity.It was found that the ionospheric mid-latitude trough,which is associated with temperature changes or enhanced ion drift,exhibited distinct characteristics.Specifically,the ionospheric mid-latitude troughs related to electron temperature(Te)peak were located more equatorward of auroral oval boundary in winter than in summer.The ionospheric mid-latitude troughs related to Te-maximum were less frequently observed at 60−70°S magnetic latitude and 90−240°E longitude.Furthermore,the troughs related to ion temperature(Ti)maximums were observed at relatively higher latitudes,occurring more frequently in winter.In addition,the troughs related to ion velocity(Vi)maximums could be observed in all seasons.The troughs with the maximum-Ti and maximum-Vi were located closer to the equatorward boundary of the auroral oval at the nightside,and in both hemispheres.This implies that enhanced ion drift velocity contributes to increased collisional frictional heating and enhanced ion temperatures,resulting in a density depletion within the trough region.
文摘Let(M,g)be a compact Riemann surface with unit area,h a smooth function on M.The Kazdan-Warner problem is that under what kind of conditions on h the equationΔu=8π-8πhe^(u) has a solution.In this survey article,we shall review the development of this problem along the variational method.
基金supported by the National Natural Science Foundation of China(Grant No.12175183)。
文摘Gamma-ray imaging systems are powerful tools in radiographic diagnosis.However,the recorded images suffer from degradations such as noise,blurring,and downsampling,consequently failing to meet high-precision diagnostic requirements.In this paper,we propose a novel single-image super-resolution algorithm to enhance the spatial resolution of gamma-ray imaging systems.A mathematical model of the gamma-ray imaging system is established based on maximum a posteriori estimation.Within the plug-and-play framework,the half-quadratic splitting method is employed to decouple the data fidelit term and the regularization term.An image denoiser using convolutional neural networks is adopted as an implicit image prior,referred to as a deep denoiser prior,eliminating the need to explicitly design a regularization term.Furthermore,the impact of the image boundary condition on reconstruction results is considered,and a method for estimating image boundaries is introduced.The results show that the proposed algorithm can effectively addresses boundary artifacts.By increasing the pixel number of the reconstructed images,the proposed algorithm is capable of recovering more details.Notably,in both simulation and real experiments,the proposed algorithm is demonstrated to achieve subpixel resolution,surpassing the Nyquist sampling limit determined by the camera pixel size.
文摘The southern region of Saudi Arabia exhibits a distinct seismic profile shaped by the Red Sea Rift and local fault systems, necessitating rigorous seismic hazard evaluations and tailored structural design strategies. This study applies a robust Probabilistic Seismic Hazard Analysis (PSHA) framework to compute Maximum Considered Earthquake (MCE) and Risk-Targeted Maximum Considered Earthquake (MCER) values for major cities, including Jazan, Abha, and Najran. Utilizing local seismotectonic models, ground motion prediction equations (GMPEs), and soil classifications, the study generates precise ground motion parameters critical for infrastructure planning and safety. Results indicate significant seismic hazard variability, with Jazan showing high seismic risks with an MCER SA (0.2 s) of 0.45 g, compared to Najran’s lower risks at 0.23 g. Structural design guidelines, informed by MCE and MCER calculations, prioritize the integration of site-specific seismic data, enhanced ductility requirements, and advanced analytical methods to ensure resilient and sustainable infrastructure. The study underscores the necessity of localized seismic assessments and modern engineering practices to effectively mitigate seismic risks in this geologically complex region.
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.
文摘The rapid expansion of tobacco farming poses a significant threat to biodiversity in Yunnan Province,China,a region known for its rich biodiversity.This study aims to understand the trade-offs between tobacco farming and higher plant species diversity,and to identify priority counties for conservation.We employed an integrated approach combining species distribution modeling,GIS overlay analysis,and empirical spatial regression to em pirically assess the impact of tobacco farming intensity on biodiversity risk.Our findings reveal a compelling negative spatial correlation between tobacco farming expansion and higher plant species diversity.Specifically,southern counties in Wenshan and Honghe prefectures are major priority areas of conservation that exhibit signif icant spatial correlations between biodiversity risks and high tobacco farming intensity.Quantitatively,at county level,a 1%increase in tobacco farming area corresponds to a 0.094%decrease in endemic higher plant species richness across the entire province.These results underscore the need for targeted and region-specific regulations to mitigate biodiversity loss and promote sustainable development in Yunnan Province.The integrated approach used in this study provides a comprehensive assessment of the tobacco-biodiversity trade-offs,offering actionable insights for policymaking.
基金Project(2024ZD1003704)supported by the Deep Earth Probe and Mineral Resources Exploration-National Science and Technology Major Project,ChinaProjects(51834001,52130404)supported by the National Natural Science Foundation of China。
文摘During upward horizontal stratified backfill mining,stable backfill is essential for cap and sill pillar recovery.Currently,the primary method for calculating the required strength of backfill is the generalized three-dimensional(3 D)vertical stress model,which ignores the effect of mine depth,failing to obtain the vertical stress at different positions along stope length.Therefore,this paper develops and validates an improved 3 D model solution through numerical simulation in Rhino-FLAC^(3D),and examines the stress state and stability of backfill under different conditions.The results show that the improved model can accurately calculate the vertical stress at different mine depths and positions along stope length.The error rates between the results of the improved model and numerical simulation are below 4%,indicating high reliability and applicability.The maximum vertical stress(σ_(zz,max))in backfill is positively correlated with the degree of rock-backfill closure,which is enhanced by mine depth and elastic modulus of backfill,while weakened by stope width and inclination,backfill friction angle,and elastic modulus of rock mass.Theσ_(zz,max)reaches its peak when the stope length is 150 m,whileσ_(zz,max)is insensitive to changes in rock-backfill interface parameters.In all cases,the backfill stability can be improved by reducingσ_(zz,max).The results provide theoretical guidance for the backfill strength design and the safe and efficient recovery of ore pillars in deep mining.
文摘Amid increasingly frequent military conflicts and explosion events,accurately predicting the dynamic response of reinforced concrete(RC) slabs,key load-bearing components in building structures,is essential for understanding blast-induced damage and enhancing structural protection.However,current approaches predominantly rely on experimental tests,finite element(FE) simulations,and conventional machine learning(ML) techniques,which are o ften costly,inefficie nt,narrowly applicable,and insufficiently accurate.To overcome these challenges,this study aims to optimize ML models,refine architectural designs,and improve model interpretability.A comprehensive dataset comprising 489 samples was constructed by integrating experimental and simulation data from existing literature,incorporating 15 input features and one target variable.Based on this dataset,a novel method,termed MOPSO-TXGBoost,was proposed.Building on XGBoost as a baseline,the method employs multiobjective particle swarm optimization(MOPSO) for hyperparameter tuning,introduces a tri-stream stacking architecture to enhance feature representation,and trains three distinct models to improve generalization performance.A weighted fusion strategy is employed to further enhance the accuracy of predictio n.Additio nally,a model comprehensive evaluation(MCE) index is introduced,which integrates error metrics and fitting performance to facilitate systematic model assessment.Experimental results indicate that,compared with the baseline XGBoost model,the proposed approach reduces prediction error by 61.4% and increases the coefficient of determination(R^(2)) by 0.217.Moreover,it outperforms several mainstream machine learning(ML) algorithms.The findings of this study advance ML-based blast damage prediction and provide theoretical support for safety assessment and protection optimization of RC slab structures.
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Derek Elsworth acknowledges the support from a Gledden Visiting Fellowship from the Institute of Advanced Studies at the University of Western Australia,Australia,and the G.Albert Shoemaker Endowment at Pennsylvania State University,USA.
文摘Triggered seismicity is a key hazard where fluids are injected or withdrawn from the subsurface and may impact permeability. Understanding the mechanisms that control fluid injection-triggered seismicity allows its mitigation. Key controls on seismicity are defined in terms of fault and fracture strength, second-order frictional response and stability, and competing fluid-driven mechanisms for arrest. We desire to constrain maximum event magnitudes in triggered earthquakes by relating pre-existing critical stresses to fluid injection volume to explain why some recorded events are significantly larger than anticipated seismic moment thresholds. This formalism is consistent with several uncharacteristically large fluid injection-triggered earthquakes. Such methods of reactivating fractures and faults by hydraulic stimulation in shear or tensile fracturing are routinely used to create permeability in the subsurface. Microearthquakes (MEQs) generated by such stimulations can be used to diagnose permeability evolution. Although high-fidelity data sets are scarce, the EGS-Collab and Utah FORGE hydraulic stimulation field demonstration projects provide high-fidelity data sets that concurrently track permeability evolution and triggered seismicity. Machine learning deciphers the principal features of MEQs and the resulting permeability evolution that best track permeability changes – with transfer learning methods allowing robust predictions across multiple eological settings. Changes in permeability at reactivated fractures in both shear and extensional modes suggest that permeability change (Δk) scales with the seismic moment (M) of individual MEQs as Δk∝M. This scaling relation is exact at early times but degrades with successive MEQs, but provides a method for characterizing crustal permeability evolution using MEQs, alone. Importantly, we quantify for the first time the role of prestress in defining the elevated magnitude and seismic moment of fluid injection-triggered events, and demonstrate that such MEQs can also be used as diagnostic in quantifying permeability evolution in the crust.
基金the National Natural Science Foundation of China(Nos.52105117,52222504&51875433)the Funds for Distinguished Young talent of Shaanxi Province,China(No.2019JC-04)。
文摘Blade Tip Timing(BTT)enables non-contact measurements of rotating blades by placing probes strategically.Due to the uneven probe layout,BTT signals exhibit periodic irregularities.While recovering parameters like frequency from such signals is possible,achieving high-precision vibration parameters remains challenging.This paper proposed a novel two-stage off-grid estimation method.It leverages a unique array layout(coprime array)to obtain a regular augmented covariance matrix.Subsequently,parameters in the matrix are recovered using the sparse iterative covariance-based estimation method based on covariance fitting criteria.Finally,high-precision estimates of imprecise parameters are obtained using unconditional maximum likelihood estimation,effectively eliminating the effects of basis mismatch.Through substantial numerical and experimental validation,the proposed method demonstrates significantly higher accuracy compared to classical BTT parameter estimation methods,approaching the lower bound of unbiased estimation variance.Furthermore,due to its immunity to frequency gridding,it can track minor frequency deviations,making it more suitable for indicating blade condition.
基金supported and funded by the Deanship of Scientifc Research at ImamMohammad Ibn Saud Islamic University(IMSIU)(grant number IMSIU-DDRSP2503).
文摘Accelerated life tests play a vital role in reliability analysis,especially as advanced technologies lead to the production of highly reliable products to meet market demands and competition.Among these tests,progressive-stress accelerated life tests(PSALT)allow for continuous changes in applied stress.Additionally,the generalized progressive hybrid censoring(GPHC)scheme has attracted significant attention in reliability and survival analysis,particularly for handling censored data in accelerated testing.It has been applied to various failure models,including competing risks and step-stress models.However,despite its growing relevance,a notable gap remains in the literature regarding the application of GPHC in PSALT models.This paper addresses that gap by studying PSALT under a GPHC scheme with binomial removal.Specifically,it considers lifetimes following the quasi-Xgamma distribution.Model parameters are estimated using both maximum likelihood and Bayesian methods under gamma priors.Interval estimation is provided through approximate confidence intervals,bootstrap methods,and Bayesian credible intervals.Bayesian estimators are derived under squared error and entropy loss functions,using informative priors in simulation and non-informative priors in real data applications.A simulation study is conducted to evaluate various censoring schemes,with coverage probabilities and interval widths assessed via Monte Carlo simulations.Additionally,Bayesian predictive estimates and intervals are presented.The proposed methodology is illustrated through the analysis of two real-world accelerated life test datasets.
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.
