The prediction of the fracture plane orientation in fatigue is a scientific topic and remains relevant for every type of material. However, in this work, we compared the orientation of the fracture plane obtained expe...The prediction of the fracture plane orientation in fatigue is a scientific topic and remains relevant for every type of material. However, in this work, we compared the orientation of the fracture plane obtained experimentally through tests on specimens under multiaxial loading with that calculated by the variance method. In the statistical approach criteria, several methods have been developed but we have presented only one method, namely the variance method using the equivalent stress. She assumes that the fracture plane orientation is the one on which the variance of the equivalent stress is maximum. Three types of equivalent stress are defined for this method [1]: normal stress, shear stress and combined normal and shear stress. The results obtained were compared with experimental results for multiaxial cyclic stress states, and it emerges that the variance method for the case of combined loading is conservative as it gives a better prediction of the fracture plane.展开更多
In the variance component estimation(VCE)of geodetic data,the problem of negative VCE is likely to occur.In the ordinary additive error model,there have been related studies to solve the problem of negative variance c...In the variance component estimation(VCE)of geodetic data,the problem of negative VCE is likely to occur.In the ordinary additive error model,there have been related studies to solve the problem of negative variance components.However,there is still no related research in the mixed additive and multiplicative random error model(MAMREM).Based on the MAMREM,this paper applies the nonnegative least squares variance component estimation(NNLS-VCE)algorithm to this model.The correlation formula and iterative algorithm of NNLS-VCE for MAMREM are derived.The problem of negative variance in VCE for MAMREM is solved.This paper uses the digital simulation example and the Digital Terrain Mode(DTM)to prove the proposed algorithm's validity.The experimental results demonstrated that the proposed algorithm can effectively correct the VCE in MAMREM when there is a negative VCE.展开更多
Working toward an efficient duration and timeline for the preconstruction phase should be one of the main objectives for project owners.Failing to plan for and coordinate preconstruction decisions in order to control ...Working toward an efficient duration and timeline for the preconstruction phase should be one of the main objectives for project owners.Failing to plan for and coordinate preconstruction decisions in order to control preconstruction duration and manage time variances can lead to financial insecurities,incomplete contract documents,permitting issues,and unrealistic schedules and resource allocation during this phase.To minimize time variances and ensure a productive decision-making process,project owners should be familiar with critical elements in a project that cause variances in the preconstruction phase timeline.In this study,the impacts of eleven critical preconstruction elements on time variances were analyzed.These eleven preconstruction elements are considered critical in how they impact time variances during the preconstruction phase.They were determined to be critical based either on significantly impacting time variance during the preconstruction phase or believed to be critical from findings from previous studies,however,the findings from this study showed no significant impact on the time variances.In most previous studies focusing on the elements impacting project schedules,data were collected by surveying construction professionals.In this study,objective and quantitative data related to project preconstruction elements were used as opposed to self-reported data.Using the results of this study,project owners and stakeholders will be able to evaluate the critical preconstruction elements impacting the timing of their projects and prioritize decisions related to the critical elements early on during the preconstruction phase.展开更多
Global variance reduction is a bottleneck in Monte Carlo shielding calculations.The global variance reduction problem requires that the statistical error of the entire space is uniform.This study proposed a grid-AIS m...Global variance reduction is a bottleneck in Monte Carlo shielding calculations.The global variance reduction problem requires that the statistical error of the entire space is uniform.This study proposed a grid-AIS method for the global variance reduction problem based on the AIS method,which was implemented in the Monte Carlo program MCShield.The proposed method was validated using the VENUS-Ⅲ international benchmark problem and a self-shielding calculation example.The results from the VENUS-Ⅲ benchmark problem showed that the grid-AIS method achieved a significant reduction in the variance of the statistical errors of the MESH grids,decreasing from 1.08×10^(-2) to 3.84×10^(-3),representing a 64.00% reduction.This demonstrates that the grid-AIS method is effective in addressing global issues.The results of the selfshielding calculation demonstrate that the grid-AIS method produced accurate computational results.Moreover,the grid-AIS method exhibited a computational efficiency approximately one order of magnitude higher than that of the AIS method and approximately two orders of magnitude higher than that of the conventional Monte Carlo method.展开更多
The effects of stochastic volatility,jump clustering,and regime switching are considered when pricing variance swaps.This study established a two-stage procedure that simplifies the derivation by first isolating the r...The effects of stochastic volatility,jump clustering,and regime switching are considered when pricing variance swaps.This study established a two-stage procedure that simplifies the derivation by first isolating the regime switching from other stochastic sources.Based on this,a novel probabilistic approach was employed,leading to pricing formulas with time-dependent and regime-switching parameters.The formulated solutions were easy to implement and differed from most existing results of variance swap pricing,where Fourier inversion or fast Fourier transform must be performed to obtain the final results,since they are completely analytical without involving integrations.The numerical results indicate that jump clustering and regime switching have a significant influence on variance swap prices.展开更多
[ Objective] The aim was to study variance type of capsule morphological characters in Platycodon grandiflorum population, and provide some theoretical basis for seeking to genetic markers which can differentiate diff...[ Objective] The aim was to study variance type of capsule morphological characters in Platycodon grandiflorum population, and provide some theoretical basis for seeking to genetic markers which can differentiate different P. grandiflorum and breeding new varieties. [ Method] According to shape morphological characters of capsule from the same population of perennial purple P. gandiflorum, seven types of distinct di- versity capsule were selected, variance analysis and multiple comparison on the length, diameter, length/diameter of the different types of capsule were carried out. [ Result] There is unicolor and bicolor, even trichrome, among main color was brown and purple. Capsule shape was main cone, furthermore, containing long roller type, spheroidicity and sphericity. [ Conclusion] P. gandiflorum capsule was divided into long form, short form and middle type from length/diameter size in perennial culture P. gandiflorum population.展开更多
An identification method using Allan variance and equivalent theorem is proposed to identify non-stationary sensor errors mixed out of different simple noises. This method firstly derives the discrete Allan variances ...An identification method using Allan variance and equivalent theorem is proposed to identify non-stationary sensor errors mixed out of different simple noises. This method firstly derives the discrete Allan variances of all component noises inherent in noise sources in terms of their different equations; then the variances are used to estimate the parameters of all component noise models; finally, the original errors are represented by the sum of the non-stationary component noise model and the equivalent m...展开更多
Rockburst precursors are critical for disaster warning,yet the complexity of rockburst has hindered the identification of a unified precursor.Furthermore,the influence of loading rates(LRs)on acoustic emission(AE)prec...Rockburst precursors are critical for disaster warning,yet the complexity of rockburst has hindered the identification of a unified precursor.Furthermore,the influence of loading rates(LRs)on acoustic emission(AE)precursors in different rock types remains poorly understood.This study investigates the AE characteristics and early warning times of rockburst in slate and mica-schist under four LRs(0.05,0.15,0.25,and 0.5 MPa/s)using true triaxial unloading tests.The micro-crack state of the samples was evaluated using entropy,while critical slowing down(CSD)theory was applied to interpret AE precursors.The results reveal that as the LR increases,the rockburst stress of both rocks initially rises and then declines,with mica-schist exhibiting more severe damage and a higher dominance of tensile cracks.Notably,identifying rockburst precursors in mica-schist proved more challenging compared to slate.Among the methods tested,AE amplitude variance outperformed entropy in precursor identification.Additionally,the rockburst early warning time was found to be negatively correlated with the LR,with mica-schist consistently showing shorter warning times than slate.The CSD-derived precursor,due to its enhanced sensitivity,is recommended for early warning systems.These findings provide new insights into the role of LRs in rockburst dynamics and offer practical guidance for improving precursor identification and disaster mitigation strategies.展开更多
Background: Resistance exercise leads to improved muscle function and metabolic homeostasis.Yet how circadian rhythm impacts exercise outcomes and its molecular transduction remains elusive.Methods: Human volunteers w...Background: Resistance exercise leads to improved muscle function and metabolic homeostasis.Yet how circadian rhythm impacts exercise outcomes and its molecular transduction remains elusive.Methods: Human volunteers were subjected to 4 weeks of resistance training protocols at different times of day to assess training outcomes and their associations with myokine irisin.Based on rhythmicity of Fibronectin type III domain containing 5(FNDC5/irisin),we trained wild type and FNDC5 knockout mice at late active phase(high FNDC5/irisin level)or late rest phase(low FNDC5/irisin level)to analyze exercise benefits on muscle function and metabolic homeostasis.Molecular analysis was performed to understand the regulatory mechanisms of FNDC5 rhythmicity and downstream signaling transduction in skeletal muscle.Results: In this study,we showed that regular resistance exercises performed at different times of day resulted in distinct training outcomes in humans,including exercise benefits and altered plasma metabolomics.We found that muscle FNDC5/irisin levels exhibit rhythmicity.Consistent with human data,compared to late rest phase(low irisin level),mice trained chronically at late active phase(high irisin level)gained more muscle capacity along with improved metabolic fitness and metabolomics/lipidomics profiles under a high-fat diet,whereas these differences were lost in FNDC5 knockout mice.Mechanistically,Basic helix-loop-helix ARNT like 1(BMAL1)and Peroxisome proliferative activated receptor,gamma,coactivator 1 alpha 4(PGC1α4)induce FNDC5/irisin transcription and rhythmicity,and the signaling is transduced viaαV integrin in muscle.Conclusion: Together,our results offered novel insights that exercise performed at distinct times of day determines training outcomes and metabolic benefits through the rhythmic regulation of the BMAL1/PGC1α4-FNDC5/irisin axis.展开更多
Scramjet is the most promising propulsion system for Air-breathing Hypersonic Vehicle(AHV),and the Infrared(IR)radiation it emits is critical for early warning,detection,and identification of such weapons.This work pr...Scramjet is the most promising propulsion system for Air-breathing Hypersonic Vehicle(AHV),and the Infrared(IR)radiation it emits is critical for early warning,detection,and identification of such weapons.This work proposes an Adaptive Reverse Monte Carlo(ARMC)method and develops an analytical model for the IR radiation of scramjet considering gaseous kerosene and hydrogen fueled conditions.The evaluation studies show that at a global equivalence ratio of 0.8,the IR radiation from hydrogen-fueled plume is predominantly from H_(2)O and spectral peak is 1.53 kW·Sr^(-1)·μm^(-1)at the 2.7μm band,while the kerosene-fueled plume exhibits a spectral intensity approaching 7.0 kW·Sr^(-1)·μm^(-1)at the 4.3μm band.At the backward detection angle,both types of scramjets exhibit spectral peaks within the 1.3-1.4μm band,with intensities around10 kW·Sr^(-1)·μm^(-1).The integral radiation intensity of hydrogen-fueled scramjet is generally higher than kerosene-fueled scramjet,particularly in 1-3μm band.Meanwhile,at wide detection angles,the solid walls become the predominant radiation source.The radiation intensity is highest in1-3μm and weakest in 8-14μm band,with values of 21.5 kW·Sr^(-1)and 0.57 kW·Sr^(-1)at the backward detection angles,respectively.Significant variations in the radiation contributions from gases and solids are observed across different bands under the two fuel conditions,especially within 3-5μm band.This research provides valuable insights into the IR radiation characteristics of scramjets,which can aid in the development of IR detection systems for AHV.展开更多
The article considers the impact of forestry machines on the soil of the cutting areas and presents the results of the impact of harvesters of different classes(middlesmall,middle and heavy)and configurations of wheel...The article considers the impact of forestry machines on the soil of the cutting areas and presents the results of the impact of harvesters of different classes(middlesmall,middle and heavy)and configurations of wheeled equipment and additional equipment on the soil of the cutting areas in the conditions of Kronoberg County(South of Sweden).Methods to reduce negative impact of wheeled harvesters on the soil of forests are proposed.The aim of the research is to assess the effect of the structural parameters of the wheel harvesters of different class on the soil of the cutting areas.Wheeled harvesters were loaded with 60 kN force.The results of experimental studies of the impact of wheeled harvesters on the forest soil are presented.Recommendations on the possibility of testing the results of research in the conditions of the rental base of the Western part of the North-Western Federal District of the Russian Federation are given.展开更多
Comparative analyses in ecology and evolution often face the challenge of controlling for the effects of shared ancestry(phylogeny)from those of ecological or trait-based predictors on species traits.Phylogenetic Gene...Comparative analyses in ecology and evolution often face the challenge of controlling for the effects of shared ancestry(phylogeny)from those of ecological or trait-based predictors on species traits.Phylogenetic Generalized Linear Models(PGLMs)address this issue by integrating phylogenetic relationships into statistical models.However,accurately partitioning explained variance among correlated predictors remains challenging.The phylolm.hp R package tackles this problem by extending the concept of“average shared variance”to PGLMs,enabling nuanced quantificationof the relative importance of phylogeny and other predictors.The package calculates individual likelihood-based R^(2) contributions of phylogeny and each predictor,accounting for both unique and shared explained variance.This approach overcomes limitations of traditional partial R^(2) methods,which often fail to sum the total R^(2) due to multicollinearity.We demonstrate the functionality of phylolm.hp through two case studies:one involving continuous trait data(maximum tree height in Californian species)and another focusing on binary trait data(species invasiveness in North American forests).The phylolm.hp package offers researchers a powerful tool to disentangle the contributions of phylogenetic and ecological predictors in comparative analyses.展开更多
Ti-6Al-4V is a lightweight,extremely strong material with high resistance to corrosion and is widely used in aerospace industries,medical implants and many more.Contour cutting in such material with sharp corner radiu...Ti-6Al-4V is a lightweight,extremely strong material with high resistance to corrosion and is widely used in aerospace industries,medical implants and many more.Contour cutting in such material with sharp corner radius,narrow kerf width,and maintaining high dimensional accuracy and surface integrity is a challenge for the modern manufacturing industry.Wire Electrical Discharge Machining(WEDM) is a feasible process to meet the above challenges.However,proper control of process parameters is highly necessary for quality cutting of such material.In order to meet the above challenges,the present work focuses on the optimum selection of different process parameters such as pulse-on time(T_(ON)),pulse-off time(T_(OFF)),spark gap voltage(SV) and wire feed rate(WF) using Taguchi-based Multi Response Signal to Noise ratio(MRSN) technique.This is a very simple multi response optimization technique to simultaneously optimize vital responses like thickness of white layer formed on the machined surfaces,average crack density,surface roughness and dimensional accuracy,without the assistance of any software.Moreover,simple regression models are developed to determine the above responses for any combination of process parameters.Industry personnel will find this study useful in utilizing this expensive non-conventional machining method in a techno-economic manner.展开更多
The Darjeeling Himalayan region,characterized by its complex topography and vulnerability to multiple environmental hazards,faces significant challenges including landslides,earthquakes,flash floods,and soil loss that...The Darjeeling Himalayan region,characterized by its complex topography and vulnerability to multiple environmental hazards,faces significant challenges including landslides,earthquakes,flash floods,and soil loss that critically threaten ecosystem stability.Among these challenges,soil erosion emerges as a silent disaster-a gradual yet relentless process whose impacts accumulate over time,progressively degrading landscape integrity and disrupting ecological sustainability.Unlike catastrophic events with immediate visibility,soil erosion’s most devastating consequences often manifest decades later through diminished agricultural productivity,habitat fragmentation,and irreversible biodiversity loss.This study developed a scalable predictive framework employing Random Forest(RF)and Gradient Boosting Tree(GBT)machine learning models to assess and map soil erosion susceptibility across the region.A comprehensive geo-database was developed incorporating 11 erosion triggering factors:slope,elevation,rainfall,drainage density,topographic wetness index,normalized difference vegetation index,curvature,soil texture,land use,geology,and aspect.A total of 2,483 historical soil erosion locations were identified and randomly divided into two sets:70%for model building and 30%for validation purposes.The models revealed distinct spatial patterns of erosion risks,with GBT classifying 60.50%of the area as very low susceptibility,while RF identified 28.92%in this category.Notable differences emerged in high-risk zone identification,with GBT highlighting 7.42%and RF indicating 2.21%as very high erosion susceptibility areas.Both models demonstrated robust predictive capabilities,with GBT achieving 80.77%accuracy and 0.975 AUC,slightly outperforming RF’s 79.67%accuracy and 0.972 AUC.Analysis of predictor variables identified elevation,slope,rainfall and NDVI as the primary factors influencing erosion susceptibility,highlighting the complex interrelationship between geo-environmental factors and erosion processes.This research offers a strategic framework for targeted conservation and sustainable land management in the fragile Himalayan region,providing valuable insights to help policymakers implement effective soil erosion mitigation strategies and support long-term environmental sustainability.展开更多
The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment.This study reported a three-dimensional electrochemical treatment ...The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment.This study reported a three-dimensional electrochemical treatment process integrating graphite intercalation compound(GIC)adsorption,direct anodic oxidation,and·OH oxidation for decolourising Reactive Black 5(RB5)from aqueous solutions.The electrochemical process was optimised using the novel progressive central composite design-response surface methodology(CCD-NPRSM),hybrid artificial neural network-extreme gradient boosting(hybrid ANN-XGBoost),and classification and regression trees(CART).CCD-NPRSM and hybrid ANN-XGBoost were employed to minimise errors in evaluating the electrochemical process involving three manipulated operational parameters:current density,electrolysis(treatment)time,and initial dye concentration.The optimised decolourisation efficiencies were 99.30%,96.63%,and 99.14%for CCD-NPRSM,hybrid ANN-XGBoost,and CART,respectively,compared to the 98.46%RB5 removal rate observed experimentally under optimum conditions:approximately 20 mA/cm^(2) of current density,20 min of electrolysis time,and 65 mg/L of RB5.The optimised mineralisation efficiencies ranged between 89%and 92%for different models based on total organic carbon(TOC).Experimental studies confirmed that the predictive efficiency of optimised models ranked in the descending order of hybrid ANN-XGBoost,CCD-NPRSM,and CART.Model validation using analysis of variance(ANOVA)revealed that hybrid ANN-XGBoost had a mean squared error(MSE)and a coefficient of determination(R^(2))of approximately 0.014 and 0.998,respectively,for the RB5 removal efficiency,outperforming CCD-NPRSM with MSE and R^(2) of 0.518 and 0.998,respectively.Overall,the hybrid ANN-XGBoost approach is the most feasible technique for assessing the electrochemical treatment efficiency in RB5 dye wastewater decolourisation.展开更多
Birefringent materials possess significant optical anisotropy,making them pivotal in modulating light polarization,particularly in laser technology and scientific applications.In this study,five variants of antimony p...Birefringent materials possess significant optical anisotropy,making them pivotal in modulating light polarization,particularly in laser technology and scientific applications.In this study,five variants of antimony potassium fluoronitrates named SbF_(3)·KNO_(3)(1),SbF_(3)·3KNO_(3)(2),SbF_(3)·3KSbF_(4)·KNO_(3)(3),KSb_(2)F_(7)·3KNO_(3)(4),and KSb_(2)F_(7)·2KNO_(3)(5)were obtained.Remarkably,each compound contains distinct Sb-polyhedra configurations.Compounds 1 and 2 consist of singular[SbF_(3)]units,compound 3 harbors a mixture of[SbF_(3)]and[SbF_(4)]units,while compounds 4 and 5 feature single[SbF_(4)]units.Interestingly,the birefringence escalates progressively from 1 to 5,and notably,compound 5 exhibits the most pronounced birefringence among all reported inorganic antimony oxysalts.Detailed structural and property analyses affirm that the structural variance among the five compounds underpins the observed differences in birefringence.Moreover,the synergistic interplay between planarπ-conjugated NO_(3)^(−)groups and Sb^(3+)ions with lone-pair electrons facilitates the emergence of substantial polarization anisotropy.展开更多
Background Although studies in recent years have explored the impact of gut microbiota on various sleep characteristics,the interaction between gut microbiota and insomnia remains unclear.Aims We aimed to evaluate the...Background Although studies in recent years have explored the impact of gut microbiota on various sleep characteristics,the interaction between gut microbiota and insomnia remains unclear.Aims We aimed to evaluate the mutual influences between gut microbiota and insomnia.Methods We conducted Mendelian randomisation(MR)analysis using genome-wide association studies datasets on insomnia(N=386533),gut microbiota data from the MiBioGen alliance(N=18340)and the Dutch Microbiome Project(N=8208).The inverse variance weighted(IVW)technique was selected as the primary approach.Then,Cochrane’s Q,Mendelian randomization-Egger(MR-Egger)and MR Pleiotropy RESidual Sum and Outlier test(MRPRESSO)tests were used to detect heterogeneity and pleiotropy.The leave-one-out method was used to test the stability of the MR results.In addition,we performed the Steiger test to thoroughly verify the causation.Results According to IVW,our results showed that 14 gut bacterial taxa may contribute to the risks of insomnia(odds ratio(OR):1.01 to 1.04),while 8 gut bacterial taxa displayed a protective effect on this condition(OR:0.97 to 0.99).Conversely,reverse MR analysis showed that insomnia may causally decrease the abundance of 7 taxa(OR:0.21 to 0.57)and increase the abundance of 12 taxa(OR:1.65 to 4.43).Notably,the genus Odoribacter showed a significant positive causal relationship after conducting the Steiger test.Cochrane’s Q test indicated no significant heterogeneity between most singlenucleotide polymorphisms.In addition,no significant level of pleiotropy was found according to MR-Egger and MRPRESSO.Conclusions Our study highlighted the reciprocal relationships between gut microbiota and insomnia,which may provide new insights into the treatment and prevention of insomnia.展开更多
The estimation of glacier flow velocity on a short-term scale is very important for further glacier dynamics research.In this study,10 Sentinel-1 ascending images and 10 Sentinel-1 descending images of Urumqi Glacier ...The estimation of glacier flow velocity on a short-term scale is very important for further glacier dynamics research.In this study,10 Sentinel-1 ascending images and 10 Sentinel-1 descending images of Urumqi Glacier No.1 in 2017 were used to calculate the glacier flow velocity in a high coherence period by DIn SAR technology and MAI technology,while the offset tracking technology was used to estimate the glacier flow velocity in a low coherence period.Then,the monthly three-dimensional flow velocity of the glacier was calculated by the Helmert variance component estimation method.Finally,the accuracy of the estimated glacier flow velocity on a monthly scale was evaluated.The results showed that:(1)the monthly scale motion velocity of Urumqi Glacier No.1 in May,June,July,and August 2017 was 0.273 m/month,0.657 m/month,0.582 m/month,and 0.392 m/month,respectively.(2)The accuracy of glacier surface velocity from May 2017 to August 2017 was 0.033 m/month,0.026 m/month,0.034 m/month and 0.037 m/month,respectively.(3)The accuracy of glacier surface flow velocity from May 2017 to August 2017 was 0.018 m/month,0.031 m/month,0.029 m/month and 0.030 m/month,respectively.Therefore,the research methodology based on the Sentinel-1 ascending and descending data and presented in this paper was applicable to the estimation of monthly-scale flow velocity of mountain glaciers.展开更多
The comprehension of universal thermodynamic behaviors in the supercritical region is crucial for examining the characteristics of black hole systems under high temperature and pressure.This study is devoted to the an...The comprehension of universal thermodynamic behaviors in the supercritical region is crucial for examining the characteristics of black hole systems under high temperature and pressure.This study is devoted to the analysis of characteristic lines and crossover behaviors within the supercritical region.By making use of the free energy,we introduce three key thermodynamic quantities:scaled variance,skewness,and kurtosis.Our results demonstrate that the Widom line,associated with the maximal scaled variance,can effectively differentiate between small and large black hole-like subphases,each displaying distinct thermodynamic behaviors within the supercritical region.Furthermore,by utilizing quasinormal modes,we identify the Frenkel line,offering a dynamic perspective to distinguish between small and large black hole-like subphases.These contribute to a deeper comprehension of black hole subphases in the supercritical region,thus illuminating new facets of black hole thermodynamics.展开更多
文摘The prediction of the fracture plane orientation in fatigue is a scientific topic and remains relevant for every type of material. However, in this work, we compared the orientation of the fracture plane obtained experimentally through tests on specimens under multiaxial loading with that calculated by the variance method. In the statistical approach criteria, several methods have been developed but we have presented only one method, namely the variance method using the equivalent stress. She assumes that the fracture plane orientation is the one on which the variance of the equivalent stress is maximum. Three types of equivalent stress are defined for this method [1]: normal stress, shear stress and combined normal and shear stress. The results obtained were compared with experimental results for multiaxial cyclic stress states, and it emerges that the variance method for the case of combined loading is conservative as it gives a better prediction of the fracture plane.
基金supported by the National Natural Science Foundation of China(No.42174011)。
文摘In the variance component estimation(VCE)of geodetic data,the problem of negative VCE is likely to occur.In the ordinary additive error model,there have been related studies to solve the problem of negative variance components.However,there is still no related research in the mixed additive and multiplicative random error model(MAMREM).Based on the MAMREM,this paper applies the nonnegative least squares variance component estimation(NNLS-VCE)algorithm to this model.The correlation formula and iterative algorithm of NNLS-VCE for MAMREM are derived.The problem of negative variance in VCE for MAMREM is solved.This paper uses the digital simulation example and the Digital Terrain Mode(DTM)to prove the proposed algorithm's validity.The experimental results demonstrated that the proposed algorithm can effectively correct the VCE in MAMREM when there is a negative VCE.
文摘Working toward an efficient duration and timeline for the preconstruction phase should be one of the main objectives for project owners.Failing to plan for and coordinate preconstruction decisions in order to control preconstruction duration and manage time variances can lead to financial insecurities,incomplete contract documents,permitting issues,and unrealistic schedules and resource allocation during this phase.To minimize time variances and ensure a productive decision-making process,project owners should be familiar with critical elements in a project that cause variances in the preconstruction phase timeline.In this study,the impacts of eleven critical preconstruction elements on time variances were analyzed.These eleven preconstruction elements are considered critical in how they impact time variances during the preconstruction phase.They were determined to be critical based either on significantly impacting time variance during the preconstruction phase or believed to be critical from findings from previous studies,however,the findings from this study showed no significant impact on the time variances.In most previous studies focusing on the elements impacting project schedules,data were collected by surveying construction professionals.In this study,objective and quantitative data related to project preconstruction elements were used as opposed to self-reported data.Using the results of this study,project owners and stakeholders will be able to evaluate the critical preconstruction elements impacting the timing of their projects and prioritize decisions related to the critical elements early on during the preconstruction phase.
基金supported by the Platform Development Foundation of the China Institute for Radiation Protection(No.YP21030101)the National Natural Science Foundation of China(General Program)(Nos.12175114,U2167209)+1 种基金the National Key R&D Program of China(No.2021YFF0603600)the Tsinghua University Initiative Scientific Research Program(No.20211080081).
文摘Global variance reduction is a bottleneck in Monte Carlo shielding calculations.The global variance reduction problem requires that the statistical error of the entire space is uniform.This study proposed a grid-AIS method for the global variance reduction problem based on the AIS method,which was implemented in the Monte Carlo program MCShield.The proposed method was validated using the VENUS-Ⅲ international benchmark problem and a self-shielding calculation example.The results from the VENUS-Ⅲ benchmark problem showed that the grid-AIS method achieved a significant reduction in the variance of the statistical errors of the MESH grids,decreasing from 1.08×10^(-2) to 3.84×10^(-3),representing a 64.00% reduction.This demonstrates that the grid-AIS method is effective in addressing global issues.The results of the selfshielding calculation demonstrate that the grid-AIS method produced accurate computational results.Moreover,the grid-AIS method exhibited a computational efficiency approximately one order of magnitude higher than that of the AIS method and approximately two orders of magnitude higher than that of the conventional Monte Carlo method.
基金supported by the National Natural Science Foundation of China(Nos.12101554,12301614),the Fundamental Research Funds for Zhejiang Provincial Universities(No.GB202103001)Zhejiang Provincial Natural Science Foundation of China(No.LQ22A010010)Ministry of Educational Social Science Foundation of China(No.21YJC880050).
文摘The effects of stochastic volatility,jump clustering,and regime switching are considered when pricing variance swaps.This study established a two-stage procedure that simplifies the derivation by first isolating the regime switching from other stochastic sources.Based on this,a novel probabilistic approach was employed,leading to pricing formulas with time-dependent and regime-switching parameters.The formulated solutions were easy to implement and differed from most existing results of variance swap pricing,where Fourier inversion or fast Fourier transform must be performed to obtain the final results,since they are completely analytical without involving integrations.The numerical results indicate that jump clustering and regime switching have a significant influence on variance swap prices.
文摘[ Objective] The aim was to study variance type of capsule morphological characters in Platycodon grandiflorum population, and provide some theoretical basis for seeking to genetic markers which can differentiate different P. grandiflorum and breeding new varieties. [ Method] According to shape morphological characters of capsule from the same population of perennial purple P. gandiflorum, seven types of distinct di- versity capsule were selected, variance analysis and multiple comparison on the length, diameter, length/diameter of the different types of capsule were carried out. [ Result] There is unicolor and bicolor, even trichrome, among main color was brown and purple. Capsule shape was main cone, furthermore, containing long roller type, spheroidicity and sphericity. [ Conclusion] P. gandiflorum capsule was divided into long form, short form and middle type from length/diameter size in perennial culture P. gandiflorum population.
基金National Basic Research Program of China (JW132006093)
文摘An identification method using Allan variance and equivalent theorem is proposed to identify non-stationary sensor errors mixed out of different simple noises. This method firstly derives the discrete Allan variances of all component noises inherent in noise sources in terms of their different equations; then the variances are used to estimate the parameters of all component noise models; finally, the original errors are represented by the sum of the non-stationary component noise model and the equivalent m...
基金supported by the National Natural Science Foundation of China(Nos.52374119,42477142 and 42277154)Natural Science Foundation of Jiangsu Province(No.BK20242059)+1 种基金the open fund of State Key Laboratory of Hydraulics and Mountain River Engineering(No.SKHL2306)the High-level Talent Introduction Project of Changzhou University(No.ZMF24020037)。
文摘Rockburst precursors are critical for disaster warning,yet the complexity of rockburst has hindered the identification of a unified precursor.Furthermore,the influence of loading rates(LRs)on acoustic emission(AE)precursors in different rock types remains poorly understood.This study investigates the AE characteristics and early warning times of rockburst in slate and mica-schist under four LRs(0.05,0.15,0.25,and 0.5 MPa/s)using true triaxial unloading tests.The micro-crack state of the samples was evaluated using entropy,while critical slowing down(CSD)theory was applied to interpret AE precursors.The results reveal that as the LR increases,the rockburst stress of both rocks initially rises and then declines,with mica-schist exhibiting more severe damage and a higher dominance of tensile cracks.Notably,identifying rockburst precursors in mica-schist proved more challenging compared to slate.Among the methods tested,AE amplitude variance outperformed entropy in precursor identification.Additionally,the rockburst early warning time was found to be negatively correlated with the LR,with mica-schist consistently showing shorter warning times than slate.The CSD-derived precursor,due to its enhanced sensitivity,is recommended for early warning systems.These findings provide new insights into the role of LRs in rockburst dynamics and offer practical guidance for improving precursor identification and disaster mitigation strategies.
基金supported by funds from National Key Research and Development Program of China (2019YFA0904500 to LX, 2023YFA1800400 to LX, and 2018YFE0113500 to JX)the National Natural Science Foundation of China (82301777 to MG, 32222024 to LX, 32325024 to XM, 32071148 to LX, and 91957116 to CX)+6 种基金Fundamental Research Funds for the Central Universities, Science and Technology Commission of Shanghai Municipality (21140904300 to XM and 22ZR1421200 to LX)Innovation Program of Shanghai Municipal Education Commission (2017-01-07-00-09-E00042 to JX)Key Project of 2022 Higher Education Scientific Research Planning Project of China Association of Higher Education (22TY0218 to FS)Youth Fund for Humanities and Social Sciences Research of the Ministry of Education (22YJC890023 to FS)Postdoctoral Fellowship Program of CPSF (GZB20230219 to MG)China Postdoctoral Science Foundation (2023M741183 to MG)ECNU public platform for Innovation (011).
文摘Background: Resistance exercise leads to improved muscle function and metabolic homeostasis.Yet how circadian rhythm impacts exercise outcomes and its molecular transduction remains elusive.Methods: Human volunteers were subjected to 4 weeks of resistance training protocols at different times of day to assess training outcomes and their associations with myokine irisin.Based on rhythmicity of Fibronectin type III domain containing 5(FNDC5/irisin),we trained wild type and FNDC5 knockout mice at late active phase(high FNDC5/irisin level)or late rest phase(low FNDC5/irisin level)to analyze exercise benefits on muscle function and metabolic homeostasis.Molecular analysis was performed to understand the regulatory mechanisms of FNDC5 rhythmicity and downstream signaling transduction in skeletal muscle.Results: In this study,we showed that regular resistance exercises performed at different times of day resulted in distinct training outcomes in humans,including exercise benefits and altered plasma metabolomics.We found that muscle FNDC5/irisin levels exhibit rhythmicity.Consistent with human data,compared to late rest phase(low irisin level),mice trained chronically at late active phase(high irisin level)gained more muscle capacity along with improved metabolic fitness and metabolomics/lipidomics profiles under a high-fat diet,whereas these differences were lost in FNDC5 knockout mice.Mechanistically,Basic helix-loop-helix ARNT like 1(BMAL1)and Peroxisome proliferative activated receptor,gamma,coactivator 1 alpha 4(PGC1α4)induce FNDC5/irisin transcription and rhythmicity,and the signaling is transduced viaαV integrin in muscle.Conclusion: Together,our results offered novel insights that exercise performed at distinct times of day determines training outcomes and metabolic benefits through the rhythmic regulation of the BMAL1/PGC1α4-FNDC5/irisin axis.
基金supported by the National Natural Science Foundation of China(No.12102356)。
文摘Scramjet is the most promising propulsion system for Air-breathing Hypersonic Vehicle(AHV),and the Infrared(IR)radiation it emits is critical for early warning,detection,and identification of such weapons.This work proposes an Adaptive Reverse Monte Carlo(ARMC)method and develops an analytical model for the IR radiation of scramjet considering gaseous kerosene and hydrogen fueled conditions.The evaluation studies show that at a global equivalence ratio of 0.8,the IR radiation from hydrogen-fueled plume is predominantly from H_(2)O and spectral peak is 1.53 kW·Sr^(-1)·μm^(-1)at the 2.7μm band,while the kerosene-fueled plume exhibits a spectral intensity approaching 7.0 kW·Sr^(-1)·μm^(-1)at the 4.3μm band.At the backward detection angle,both types of scramjets exhibit spectral peaks within the 1.3-1.4μm band,with intensities around10 kW·Sr^(-1)·μm^(-1).The integral radiation intensity of hydrogen-fueled scramjet is generally higher than kerosene-fueled scramjet,particularly in 1-3μm band.Meanwhile,at wide detection angles,the solid walls become the predominant radiation source.The radiation intensity is highest in1-3μm and weakest in 8-14μm band,with values of 21.5 kW·Sr^(-1)and 0.57 kW·Sr^(-1)at the backward detection angles,respectively.Significant variations in the radiation contributions from gases and solids are observed across different bands under the two fuel conditions,especially within 3-5μm band.This research provides valuable insights into the IR radiation characteristics of scramjets,which can aid in the development of IR detection systems for AHV.
文摘The article considers the impact of forestry machines on the soil of the cutting areas and presents the results of the impact of harvesters of different classes(middlesmall,middle and heavy)and configurations of wheeled equipment and additional equipment on the soil of the cutting areas in the conditions of Kronoberg County(South of Sweden).Methods to reduce negative impact of wheeled harvesters on the soil of forests are proposed.The aim of the research is to assess the effect of the structural parameters of the wheel harvesters of different class on the soil of the cutting areas.Wheeled harvesters were loaded with 60 kN force.The results of experimental studies of the impact of wheeled harvesters on the forest soil are presented.Recommendations on the possibility of testing the results of research in the conditions of the rental base of the Western part of the North-Western Federal District of the Russian Federation are given.
基金supported by the National Natural Science Foundation of China(32271551,32571954)National Key Research and Development Program of China(2023YFF0805800)the Metasequoia funding of Nanjing Forestry University.
文摘Comparative analyses in ecology and evolution often face the challenge of controlling for the effects of shared ancestry(phylogeny)from those of ecological or trait-based predictors on species traits.Phylogenetic Generalized Linear Models(PGLMs)address this issue by integrating phylogenetic relationships into statistical models.However,accurately partitioning explained variance among correlated predictors remains challenging.The phylolm.hp R package tackles this problem by extending the concept of“average shared variance”to PGLMs,enabling nuanced quantificationof the relative importance of phylogeny and other predictors.The package calculates individual likelihood-based R^(2) contributions of phylogeny and each predictor,accounting for both unique and shared explained variance.This approach overcomes limitations of traditional partial R^(2) methods,which often fail to sum the total R^(2) due to multicollinearity.We demonstrate the functionality of phylolm.hp through two case studies:one involving continuous trait data(maximum tree height in Californian species)and another focusing on binary trait data(species invasiveness in North American forests).The phylolm.hp package offers researchers a powerful tool to disentangle the contributions of phylogenetic and ecological predictors in comparative analyses.
文摘Ti-6Al-4V is a lightweight,extremely strong material with high resistance to corrosion and is widely used in aerospace industries,medical implants and many more.Contour cutting in such material with sharp corner radius,narrow kerf width,and maintaining high dimensional accuracy and surface integrity is a challenge for the modern manufacturing industry.Wire Electrical Discharge Machining(WEDM) is a feasible process to meet the above challenges.However,proper control of process parameters is highly necessary for quality cutting of such material.In order to meet the above challenges,the present work focuses on the optimum selection of different process parameters such as pulse-on time(T_(ON)),pulse-off time(T_(OFF)),spark gap voltage(SV) and wire feed rate(WF) using Taguchi-based Multi Response Signal to Noise ratio(MRSN) technique.This is a very simple multi response optimization technique to simultaneously optimize vital responses like thickness of white layer formed on the machined surfaces,average crack density,surface roughness and dimensional accuracy,without the assistance of any software.Moreover,simple regression models are developed to determine the above responses for any combination of process parameters.Industry personnel will find this study useful in utilizing this expensive non-conventional machining method in a techno-economic manner.
文摘The Darjeeling Himalayan region,characterized by its complex topography and vulnerability to multiple environmental hazards,faces significant challenges including landslides,earthquakes,flash floods,and soil loss that critically threaten ecosystem stability.Among these challenges,soil erosion emerges as a silent disaster-a gradual yet relentless process whose impacts accumulate over time,progressively degrading landscape integrity and disrupting ecological sustainability.Unlike catastrophic events with immediate visibility,soil erosion’s most devastating consequences often manifest decades later through diminished agricultural productivity,habitat fragmentation,and irreversible biodiversity loss.This study developed a scalable predictive framework employing Random Forest(RF)and Gradient Boosting Tree(GBT)machine learning models to assess and map soil erosion susceptibility across the region.A comprehensive geo-database was developed incorporating 11 erosion triggering factors:slope,elevation,rainfall,drainage density,topographic wetness index,normalized difference vegetation index,curvature,soil texture,land use,geology,and aspect.A total of 2,483 historical soil erosion locations were identified and randomly divided into two sets:70%for model building and 30%for validation purposes.The models revealed distinct spatial patterns of erosion risks,with GBT classifying 60.50%of the area as very low susceptibility,while RF identified 28.92%in this category.Notable differences emerged in high-risk zone identification,with GBT highlighting 7.42%and RF indicating 2.21%as very high erosion susceptibility areas.Both models demonstrated robust predictive capabilities,with GBT achieving 80.77%accuracy and 0.975 AUC,slightly outperforming RF’s 79.67%accuracy and 0.972 AUC.Analysis of predictor variables identified elevation,slope,rainfall and NDVI as the primary factors influencing erosion susceptibility,highlighting the complex interrelationship between geo-environmental factors and erosion processes.This research offers a strategic framework for targeted conservation and sustainable land management in the fragile Himalayan region,providing valuable insights to help policymakers implement effective soil erosion mitigation strategies and support long-term environmental sustainability.
文摘The highly efficient electrochemical treatment technology for dye-polluted wastewater is one of hot research topics in industrial wastewater treatment.This study reported a three-dimensional electrochemical treatment process integrating graphite intercalation compound(GIC)adsorption,direct anodic oxidation,and·OH oxidation for decolourising Reactive Black 5(RB5)from aqueous solutions.The electrochemical process was optimised using the novel progressive central composite design-response surface methodology(CCD-NPRSM),hybrid artificial neural network-extreme gradient boosting(hybrid ANN-XGBoost),and classification and regression trees(CART).CCD-NPRSM and hybrid ANN-XGBoost were employed to minimise errors in evaluating the electrochemical process involving three manipulated operational parameters:current density,electrolysis(treatment)time,and initial dye concentration.The optimised decolourisation efficiencies were 99.30%,96.63%,and 99.14%for CCD-NPRSM,hybrid ANN-XGBoost,and CART,respectively,compared to the 98.46%RB5 removal rate observed experimentally under optimum conditions:approximately 20 mA/cm^(2) of current density,20 min of electrolysis time,and 65 mg/L of RB5.The optimised mineralisation efficiencies ranged between 89%and 92%for different models based on total organic carbon(TOC).Experimental studies confirmed that the predictive efficiency of optimised models ranked in the descending order of hybrid ANN-XGBoost,CCD-NPRSM,and CART.Model validation using analysis of variance(ANOVA)revealed that hybrid ANN-XGBoost had a mean squared error(MSE)and a coefficient of determination(R^(2))of approximately 0.014 and 0.998,respectively,for the RB5 removal efficiency,outperforming CCD-NPRSM with MSE and R^(2) of 0.518 and 0.998,respectively.Overall,the hybrid ANN-XGBoost approach is the most feasible technique for assessing the electrochemical treatment efficiency in RB5 dye wastewater decolourisation.
基金supported by the National Natural Science Foundation of China(Nos.22122106,22071158,22375139,22305166).
文摘Birefringent materials possess significant optical anisotropy,making them pivotal in modulating light polarization,particularly in laser technology and scientific applications.In this study,five variants of antimony potassium fluoronitrates named SbF_(3)·KNO_(3)(1),SbF_(3)·3KNO_(3)(2),SbF_(3)·3KSbF_(4)·KNO_(3)(3),KSb_(2)F_(7)·3KNO_(3)(4),and KSb_(2)F_(7)·2KNO_(3)(5)were obtained.Remarkably,each compound contains distinct Sb-polyhedra configurations.Compounds 1 and 2 consist of singular[SbF_(3)]units,compound 3 harbors a mixture of[SbF_(3)]and[SbF_(4)]units,while compounds 4 and 5 feature single[SbF_(4)]units.Interestingly,the birefringence escalates progressively from 1 to 5,and notably,compound 5 exhibits the most pronounced birefringence among all reported inorganic antimony oxysalts.Detailed structural and property analyses affirm that the structural variance among the five compounds underpins the observed differences in birefringence.Moreover,the synergistic interplay between planarπ-conjugated NO_(3)^(−)groups and Sb^(3+)ions with lone-pair electrons facilitates the emergence of substantial polarization anisotropy.
文摘Background Although studies in recent years have explored the impact of gut microbiota on various sleep characteristics,the interaction between gut microbiota and insomnia remains unclear.Aims We aimed to evaluate the mutual influences between gut microbiota and insomnia.Methods We conducted Mendelian randomisation(MR)analysis using genome-wide association studies datasets on insomnia(N=386533),gut microbiota data from the MiBioGen alliance(N=18340)and the Dutch Microbiome Project(N=8208).The inverse variance weighted(IVW)technique was selected as the primary approach.Then,Cochrane’s Q,Mendelian randomization-Egger(MR-Egger)and MR Pleiotropy RESidual Sum and Outlier test(MRPRESSO)tests were used to detect heterogeneity and pleiotropy.The leave-one-out method was used to test the stability of the MR results.In addition,we performed the Steiger test to thoroughly verify the causation.Results According to IVW,our results showed that 14 gut bacterial taxa may contribute to the risks of insomnia(odds ratio(OR):1.01 to 1.04),while 8 gut bacterial taxa displayed a protective effect on this condition(OR:0.97 to 0.99).Conversely,reverse MR analysis showed that insomnia may causally decrease the abundance of 7 taxa(OR:0.21 to 0.57)and increase the abundance of 12 taxa(OR:1.65 to 4.43).Notably,the genus Odoribacter showed a significant positive causal relationship after conducting the Steiger test.Cochrane’s Q test indicated no significant heterogeneity between most singlenucleotide polymorphisms.In addition,no significant level of pleiotropy was found according to MR-Egger and MRPRESSO.Conclusions Our study highlighted the reciprocal relationships between gut microbiota and insomnia,which may provide new insights into the treatment and prevention of insomnia.
基金funded by the Basic scientific research fund projects(Youth Project)of the Educational Department of Liaoning Province in 2023(Grants No.JYTQN2023451)Liaoning Institute of Science and Technology doctoral research initiation fund project in 2023(Grants No.2307B27)+2 种基金Basic Research Project of Higher Education Institutions of Liaoning Provincial Department of Education(Grants No.2024JYTYB-12)the Basic scientific research fund projects(Youth Project)of the Educational Department of Liaoning Province in 2023(Grants No.JYTQN2024-21)Liaoning Institute of Science and Technology doctoral research initiation fund project in 2023(Grants No.2307B26)。
文摘The estimation of glacier flow velocity on a short-term scale is very important for further glacier dynamics research.In this study,10 Sentinel-1 ascending images and 10 Sentinel-1 descending images of Urumqi Glacier No.1 in 2017 were used to calculate the glacier flow velocity in a high coherence period by DIn SAR technology and MAI technology,while the offset tracking technology was used to estimate the glacier flow velocity in a low coherence period.Then,the monthly three-dimensional flow velocity of the glacier was calculated by the Helmert variance component estimation method.Finally,the accuracy of the estimated glacier flow velocity on a monthly scale was evaluated.The results showed that:(1)the monthly scale motion velocity of Urumqi Glacier No.1 in May,June,July,and August 2017 was 0.273 m/month,0.657 m/month,0.582 m/month,and 0.392 m/month,respectively.(2)The accuracy of glacier surface velocity from May 2017 to August 2017 was 0.033 m/month,0.026 m/month,0.034 m/month and 0.037 m/month,respectively.(3)The accuracy of glacier surface flow velocity from May 2017 to August 2017 was 0.018 m/month,0.031 m/month,0.029 m/month and 0.030 m/month,respectively.Therefore,the research methodology based on the Sentinel-1 ascending and descending data and presented in this paper was applicable to the estimation of monthly-scale flow velocity of mountain glaciers.
基金supported by the National Natural Science Foundation of China(Grant Nos.12473001,11975072,11875102,11835009,and 11965013)the National SKA Program of China(Grant Nos.2022SKA0110200 and 2022SKA0110203)+1 种基金the National 111 Project(Grant No.B16009)supported by Yunnan High-level Talent Training Support Plan Young&Elite Talents Project(Grant No.YNWR-QNBJ-2018-181).
文摘The comprehension of universal thermodynamic behaviors in the supercritical region is crucial for examining the characteristics of black hole systems under high temperature and pressure.This study is devoted to the analysis of characteristic lines and crossover behaviors within the supercritical region.By making use of the free energy,we introduce three key thermodynamic quantities:scaled variance,skewness,and kurtosis.Our results demonstrate that the Widom line,associated with the maximal scaled variance,can effectively differentiate between small and large black hole-like subphases,each displaying distinct thermodynamic behaviors within the supercritical region.Furthermore,by utilizing quasinormal modes,we identify the Frenkel line,offering a dynamic perspective to distinguish between small and large black hole-like subphases.These contribute to a deeper comprehension of black hole subphases in the supercritical region,thus illuminating new facets of black hole thermodynamics.
