Vessel motions in offshore operations are heavily influenced by uncertain wave loads and hydrodynamic parameters.Yet,traditional deterministic or probabilistic models often fail to capture epistemic ambiguity when dat...Vessel motions in offshore operations are heavily influenced by uncertain wave loads and hydrodynamic parameters.Yet,traditional deterministic or probabilistic models often fail to capture epistemic ambiguity when data are scarce.We introduce a fuzzy–set framework usingα-cut interval analysis to represent imprecise wave heights,periods,added mass,damping,and stiffness as fuzzy numbers.These are incorporated into the multi-body equations of motion and solved via a fuzzy Runge–Kutta scheme across nestedα-levels.A simulation architecture iterates overα-cuts and time-steps to produce interval bounds on heavy responses.A case study off the Karnataka coast,with realistic sea-state data for moderate and severe scenarios,yields heave-amplitude envelopes whose widths quantify response uncertainty.At mid-confidence(α=0.5),moderate seas produce amplitudes of 8.30–9.65 m(±15%),while severe seas yield 7.15–8.90 m(±22%).Envelope narrowing asα→1 confirms that increased parameter confidence reduces prediction spread,and bias analysis against crisp baselines highlights the impact of imprecision on mean responses.This non-probabilistic approach provides interpretable,worst-and best-case motion bounds without requiring large datasets,offering marine engineers robust safety margins and guidance for targeted data collection and real-time uncertainty updating.展开更多
This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theo...This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theorem,fixed point index theory and the analytic technique,we give the bifurcation point of the parameter which divides the range of parameter for the existence of at least two,one and no positive solutions for the problem.And,by using a fixed point theorem of generalized concave operator and cone theory,we establish the maximum parameter interval for the existence of the unique positive solution for the problem and show that such a positive solution continuously depends on the parameter.In the end,some examples are given to illustrate our main results.展开更多
Composite resin restorations are routinely exposed to acidic and chromogenic beverages that may alter their surface integrity over time.This in-vitro study evaluated the surface roughness behavior of two universal sin...Composite resin restorations are routinely exposed to acidic and chromogenic beverages that may alter their surface integrity over time.This in-vitro study evaluated the surface roughness behavior of two universal single-shade(Unishade)composites and two conventionalmulti-shade composites following immersion in commonly consumed staining solutions and assessed whether repolishing could restore smoothness after degradation.A total of 120 standardized disc specimens were fabricated and allocated to fourmaterial groups,with each group subdivided into distilled water,cola,and coffee immersion subgroups.Surface roughness was recorded at baseline,after one week,after one month,and following a final repolishing step using a standardized multi-step system.The findings demonstrated that Unishade composites exhibited more stable surface characteristics across all immersion periods,with changes consistently remaining below the threshold associated with biofilm accumulation.Conventional composites showed greater variability,particularly in cola,where roughness values increased significantly compared with distilled water and coffee.Repolishing substantially reduced immersion-induced roughness in all materials,although its effectiveness varied depending on composite formulation and beverage acidity.Cola produced the greatest surface alterations across all groups,highlighting the erosive potential of low-pH beverages.These results indicate that Unishade composites possess superior resistance to surface degradation,likely due to their nano-structured filler configuration and less hydrophilic resin matrices,while conventional materials appear more susceptible to acidic challenge.Within the limitations of this study,selecting surface-stable material types and applying appropriate finishing and repolishing protocols may enhance the long-term performance and esthetics of composite restorations.展开更多
Crossflow instability will be present when the vehicle has an angle of attack in hypersonic flow,and it might play a dominant role in hypersonic boundary layer transition.By far the mechanism of crossflow instability-...Crossflow instability will be present when the vehicle has an angle of attack in hypersonic flow,and it might play a dominant role in hypersonic boundary layer transition.By far the mechanism of crossflow instability-induced hypersonic boundary layer transition is still out of understanding,although the large effort has been devoted.Upon this work,the overall roughness effect on instabilities in hypersonic flow was researched experimentally.Surface flush-mounted pressure sensors and infrared camera were employed to investigate the instability waves when different rough surfaces were deployed.The results reveal that the moderate surface roughness level on cone model can suppress the growth of crossflow instabilities at certain azimuthal angles in hypersonic flow.展开更多
Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sen...Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sensitive to long-wavelength(15–120 m)and lateral irregularities,which are often overlooked in traditional roughness models.This study aims to construct a three-dimensional runway roughness modeling framework integrating"precise detection-spectrum analysis-spatial reconstruction"in response to this issue.Combining the elevation data of 37 runways(5 asphalt runways and 32 cement runways)measured by a vehicle-mounted laser profilometer and the BeiDou positioning system,the power spectrum analysis was carried out by the Burg method and the spectrum models of asphalt and cement runways were fitted respectively.Meanwhile,a new exponential lateral coherence function was proposed.Finally,the three-dimensional spatial model was reconstructed by using the transfer function and genetic algorithm.The results show that the error of the measured elevation data is less than 1 cm.The spectral characteristics of different pavement types are significantly different.Among them,the R^(2) of the asphalt runway fitted with the Sussman model is greater than 0.9.The cement runway needs to be characterized by a piecewise function to represent the spectral mutation.The fitting error of the new index's lateral coherence function has been reduced to 0.012.The reconstructed three-dimensional model is in good agreement with the theoretical value and the error does not exceed 0.18 mm^(2) m/c.Finally,a three-dimensional model of 0–20 m in the lateral direction and 3000 m in the longitudinal direction is generated,providing support for aircraft vibration simulation and pavement maintenance.展开更多
Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogen...Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.展开更多
Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competiti...Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competitiveness of China’s marine science sector.However,research on the competitiveness of RMIE is limited.To this end,this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of RMIE in China from 2008 to 2020.The findings indicate generally fluctuating upward trends in RMIE’s competitiveness,with Shandong,Jiangsu,and Guangdong showing relatively strong positions.Notably,there are significant intra-regional imbalances and inter-regional asynchrony in RMIE’s competitiveness across China’s three major marine economic circles.Recognizing that forecasting RMIE competitiveness can inform policy formulation,this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects.This model effectively captures the interval and uncertainty characteristics of RMIE’s competitiveness while considering spatial relationships among regions.Results from comparative analysis,robustness tests,and sensitivity analysis demonstrate its superior applicability and forecasting accuracy.Additionally,interval forecasts and scenario analyses suggest that RMIE competitiveness will maintain stable growth,although unbalanced and unsynchronized development is likely to persist.Overall,the approach developed for evaluating and forecasting RMIE competitiveness offers valuable insights for effective policy formulation.展开更多
A genetic linkage map with 89 SSR marker loci was constructed based on a maize (Zea mays L.) population consisting of 184 F-2 individuals from the cross, Huangzao 4 X Ye 107. The 184 F-3 families were evaluated in the...A genetic linkage map with 89 SSR marker loci was constructed based on a maize (Zea mays L.) population consisting of 184 F-2 individuals from the cross, Huangzao 4 X Ye 107. The 184 F-3 families were evaluated in the field under well-watered and drought-stressed regimes in Shanxi Province of China. The objectives of the study were to identify genetic segments responsible for the expression of anthesis-silking interval (ASI), ear setting and grain yield, and to examine if the quantitative trait loci (QTLs) for ASI or yield components can be used in marker-assisted selection (MAS) to improve grain yield under drought conditions. Results showed that under well-watered and drought-stressed regimes, three and two QTLs involved in the expression of ASI were detected on chromosomes 1, 2 and 3, and 2 and 5, respectively. Under well-watered regime, two QTLs for ear setting were detected on chromosomes 3 and 6, explaining about 19.9% of the phenotypic variance, and displayed additive and partial dominant effects, respectively. Under drought-stressed condition, four QTLs for ear setting were detected on chromosomes 3, 7 and 10, which were responsible for interpreting 60.4% of the phenotypic variance, and showed dominant or partial dominant effects. Under well-watered condition, four QTLs controlling grain yield were identified on chromosomes 3, 6 and 7, while five QTLs were identified under drought stress on chromosomes 1, 2, 4 and 8. The gene action was of additive or partial dominant effects, and each QTL could explain 7.3% to 22.0% of the phenotypic variance, respectively. Under drought conditions, ASI and ear setting percentage were highly correlated with grain yield, which can be used as secondary traits for grain yield selection. Based on linked markers detected and gene action analyzed, an MAS strategy for yield improvement under drought condition could be established, which consists of QTLs contributing to decreased ASI and to increased ear setting and grain yield, respectively.展开更多
A field study was conducted on the experimental farm of ministry of agriculture, located at Palestine Technical University-Kadoorie, to investigate the effects of saline water irrigation through three irrigation inter...A field study was conducted on the experimental farm of ministry of agriculture, located at Palestine Technical University-Kadoorie, to investigate the effects of saline water irrigation through three irrigation intervals on yield of tomato crop and soil properties. The land was prepared and divided into 12 treatments, each of 48 square meters on the first of April. Tomato seedlings were planted on 25 April 2010;the seedlings were irrigated with fresh water for a period of 10 days after planting. Three levels of saline water irrigation (3, 5, 7 dS/m) plus fresh water as control were applied during the growing season. The four irrigation water treatments were applied through three irrigation intervals (every day, every second day and every three days). Gravimetric soil moisture content and soil electrical conductivity were monitored every two weeks during the growing period. Yield measurements were taken for total fruit yield, marketable yield as a percent of total yield, and average fruit weight of each treatment. Results of this study indicated that, plant treatments irrigated with saline water gave the highest yield for treatments irrigated every day compared to the treatments irrigated every second day and every three days. Statistical analysis showed significant differences in yield reduction between every second day and every three days irrigation intervals under 5 and 7 dS/m saline irrigation levels, while there was no significant difference between irrigation intervals under 3 dS/m salinity level.展开更多
According to the American Heart Association’s (AHA) recent statistical update, over 2150 Americans die each day from cardiovascular disease (CVD), which equals approximately 1 death every 40 seconds;many of which wer...According to the American Heart Association’s (AHA) recent statistical update, over 2150 Americans die each day from cardiovascular disease (CVD), which equals approximately 1 death every 40 seconds;many of which were under the age of 65 years old [1]. In 2009, 386,324 people, 1 in 6 Americans, died as a result of coronary artery disease (CAD) alone [1]. They also estimate 150,000 people have “silent” heart attacks each year [1]. Even though the number of cardiovascular disease deaths has declined in the last 10 years, they still accounted for 32.3% of American deaths [1]. As a result, the AHA updated their 2020 goals to improve the nation’s cardiovascular health by 20% [1]. One of these methods is through the use of cardiac rehabilitation. Cardiac rehabilitation (CR) is a health promotion strategy to help return cardiac patients to their previous level of functioning, increase health, decrease comorbidities and promote education and lifestyle change. For select patients, another alternative exercise plan may exist to gain even better results. High intensity interval training (HIIT) has shown positive training results for athletes and many studies show that it may also be an effective exercise modality for many cardiac patients instead of the traditional circuit training method. This article will review current literature on the effects of HIIT on CR patients as well as a sample HIIT protocol for instituting this treatment with appropriate patients.展开更多
This paper combines interval-valued intuitionistic fuzzy sets and rough sets.It studies rougheness in interval-valued intuitionistic fuzzy sets and proposes one kind of interval-valued intuitionistic fuzzy-rough sets ...This paper combines interval-valued intuitionistic fuzzy sets and rough sets.It studies rougheness in interval-valued intuitionistic fuzzy sets and proposes one kind of interval-valued intuitionistic fuzzy-rough sets models under the equivalence relation in crisp sets.That extends the classical rough set defined by Pawlak.展开更多
Fusing the structure feature of interval concept lattice and the actual needs of rough control rules,we have constructed the decision interval concept lattice,further more,we also have built a rules mining model of ro...Fusing the structure feature of interval concept lattice and the actual needs of rough control rules,we have constructed the decision interval concept lattice,further more,we also have built a rules mining model of rough control based on decision interval concept lattice,in order to achieve the optimality between rough control mining cost and control efficiency.Firstly,we have preprocessed the collected original data,so that we can transform it into Boolean formal context form,and then we have constructed the decision interval concept lattice in rough control;secondly,we have established the control rules mining algorithm based on decision interval concept lattice.By analyzing and judging redundant rules,we have formed the rough control association rule base in end.Analysis shows that under the premise of improving the reliability of rules,we have achieved the rough control optimization goal between cost and efficiency.Finally,the model of reservoir scheduling has verified its feasibility and efficiency.展开更多
This paper proposes an optimal failure-finding interval （FFI） model based on maximizing expected availability. The model can be viewed as an extension and improvement to the model presented in Moubray （1997）. Nume...This paper proposes an optimal failure-finding interval （FFI） model based on maximizing expected availability. The model can be viewed as an extension and improvement to the model presented in Moubray （1997）. Numerical results are also included to illustrate the appropriateness of the proposed model.展开更多
Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC...Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.展开更多
To address prediction errors and limited information extraction in machine learning(ML)-based interval prediction,a hybrid model was proposed for interval estimation and failure assessment of step-like landslides unde...To address prediction errors and limited information extraction in machine learning(ML)-based interval prediction,a hybrid model was proposed for interval estimation and failure assessment of step-like landslides under uncertainty.The model decomposed displacements into trend and periodic components via Variational Mode Decomposition(VMD)and K-shape clustering.The Residual and Moving Block Bootstrap methods were used to generate pseudo datasets.Polynomial regressionwas adopted for trend forecasting,whereas the Dense Convolutional Network(DenseNet)and Long Short-Term Memory(LSTM)networks were employed for periodic displacement prediction.An Extreme Learning Machine(ELM)was used to estimate the noise variance,enabling the construction of Prediction Intervals(PIs)and quantificationof displacement uncertainty.Failure probabilities(Pf)were derived from PIs using an improved tangential angle criterion and reliability analysis.The model was validated on three step-like landslides in the Three Gorges Reservoir Area,achieving stability assessment accuracies of 99.88%(XD01),99.93%(ZG93),99.89%(ZG118),and 100%for ZG110 and ZG111 across the Baishuihe and Bazimen landslides.For the Shuping landslide,the predictions aligned with fieldobservations before and after the 2014–2015 remediation,with P_(f)remaining near zero post-2015 except for occasional peaks.The model outperformed conventional ML approaches by yielding narrower PIs.At XD01 with 90%PI nominal confidencelevel(PINC),the coverage width-based criterion(CWC)and PI average width(PIAW)were 3.38 mm.The mean values of the PIs exhibited high accuracy,with a Mean Absolute Error(MAE)of 0.28 mm and Root Mean Square Error(RMSE)of 0.39 mm.These results demonstrate the robustness of the proposed model in improving landslide risk assessment and decision-making under uncertainty.展开更多
The roughness of the fracture surface directly affects the strength,deformation,and permeability of the surrounding rock in deep underground engineering.Understanding the effect of high temperature and thermal cycle o...The roughness of the fracture surface directly affects the strength,deformation,and permeability of the surrounding rock in deep underground engineering.Understanding the effect of high temperature and thermal cycle on the fracture surface roughness plays an important role in estimating the damage degree and stability of deep rock mass.In this paper,the variations of fracture surface roughness of granite after different heating and thermal cycles were investigated using the joint roughness coefficient method(JRC),three-dimensional(3D)roughness parameters,and fractal dimension(D),and the mechanism of damage and deterioration of granite were revealed.The experimental results show an increase in the roughness of the granite fracture surface as temperature and cycle number were incremented.The variations of JRC,height parameter,inclination parameter and area parameter with the temperature conformed to the Boltzmann's functional distribution,while the D decreased linearly as the temperature increased.Besides,the anisotropy index(Ip)of the granite fracture surface increased as the temperature increased,and the larger parameter values of roughness characterization at different temperatures were attained mainly in directions of 20°–40°,60°–100°and 140°–160°.The fracture aperture of granite after fracture followed the Gauss distribution and the average aperture increased with increasing temperature,which increased from 0.665 mm at 25℃to 1.058 mm at 800℃.High temperature caused an uneven thermal expansion,water evaporation,and oxidation of minerals within the granite,which promoted the growth and expansion of microfractures,and reduced interparticle bonding strength.In particular,the damage was exacerbated by the expansion and cracking of the quartz phase transition after T>500℃.Thermal cycles contributed to the accumulation of this damage and further weakened the interparticle bonding forces,resulting in a significant increase in the roughness,anisotropy,and aperture of the fracture surface after five cycles.展开更多
Workpiece rotational grinding is widely used in the ultra-precision machining of hard and brittle semiconductor materials,including single-crystal silicon,silicon carbide,and gallium arsenide.Surface roughness and sub...Workpiece rotational grinding is widely used in the ultra-precision machining of hard and brittle semiconductor materials,including single-crystal silicon,silicon carbide,and gallium arsenide.Surface roughness and subsurface damage depth(SDD)are crucial indicators for evaluating the surface quality of these materials after grinding.Existing prediction models lack general applicability and do not accurately account for the complex material behavior under grinding conditions.This paper introduces novel models for predicting both surface roughness and SDD in hard and brittle semiconductor materials.The surface roughness model uniquely incorporates the material’s elastic recovery properties,revealing the significant impact of these properties on prediction accuracy.The SDD model is distinguished by its analysis of the interactions between abrasive grits and the workpiece,as well as the mechanisms governing stress-induced damage evolution.The surface roughness model and SDD model both establish a stable relationship with the grit depth of cut(GDC).Additionally,we have developed an analytical relationship between the GDC and grinding process parameters.This,in turn,enables the establishment of an analytical framework for predicting surface roughness and SDD based on grinding process parameters,which cannot be achieved by previous models.The models were validated through systematic experiments on three different semiconductor materials,demonstrating excellent agreement with experimental data,with prediction errors of 6.3%for surface roughness and6.9%for SDD.Additionally,this study identifies variations in elastic recovery and material plasticity as critical factors influencing surface roughness and SDD across different materials.These findings significantly advance the accuracy of predictive models and broaden their applicability for grinding hard and brittle semiconductor materials.展开更多
With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation ...With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation and load.Accounting for these issues,this paper proposes a multi-timescale coordinated optimization dispatch method for distribution networks.First,the probability box theory was employed to determine the uncertainty intervals of generation and load forecasts,based on which,the requirements for flexibility dispatch and capacity constraints of the grid were calculated and analyzed.Subsequently,a multi-timescale optimization framework was constructed,incorporating the generation and load forecast uncertainties.This framework included optimization models for dayahead scheduling,intra-day optimization,and real-time adjustments,aiming to meet flexibility needs across different timescales and improve the economic efficiency of the grid.Furthermore,an improved soft actor-critic algorithm was introduced to enhance the uncertainty exploration capability.Utilizing a centralized training and decentralized execution framework,a multi-agent SAC network model was developed to improve the decision-making efficiency of the agents.Finally,the effectiveness and superiority of the proposed method were validated using a modified IEEE-33 bus test system.展开更多
The scale effect on shear strength of rock joints is well-documented.However,whether scale effects are negative,positive,or even exist or not is still controversial.Joint roughness significantly influences the shear s...The scale effect on shear strength of rock joints is well-documented.However,whether scale effects are negative,positive,or even exist or not is still controversial.Joint roughness significantly influences the shear strength of rock joints.Compared to the shear tests,using the joint roughness coefficient(JRC)and its roughness parameters offers a more convenient method for describing the scale effect on shear strength.However,it is crucial to understand that the scale effect mechanisms of JRC are distinct from those of shear strength.Therefore,this paper aims to clarify these distinct mechanisms.By digitally extracting roughness parameters from granite samples,it is found that the scale effect of roughness parameters mainly comes from the sampling methods and the geometric characteristics of parameters.Furthermore,a full data sampling method considering heterogeneity is proposed to obtain more representative roughness parameters.To reveal the scale effect mechanisms of shear strength,Gaussian filtering is firstly used to separate the waviness and unevenness components of roughness,facilitating a deeper understanding of the geometric characteristics of roughness.It is suggested that the wavelength of the waviness component can reflect the scale effect on shear strength.Secondly,numerical simulations of ideal artificial joint models are conducted to validate that the wavelength of the waviness component serves as the dividing point between positive and negative scale effects.The mechanical mechanisms of positive and negative scale effects are also interpreted.Finally,these mechanisms successfully elucidate the occurrence patterns of the scale effect on natural joint profiles.展开更多
Let Ω be homogeneous of degree zero,integrable on S^(n−1) and have mean value zero,T_(Ω) be the homogeneous singular integral operator with kernel Ω(x)/|x|^(n) and[b,T_(Ω)]be the commutator of T_(Ω)with symbol b∈BMO(...Let Ω be homogeneous of degree zero,integrable on S^(n−1) and have mean value zero,T_(Ω) be the homogeneous singular integral operator with kernel Ω(x)/|x|^(n) and[b,T_(Ω)]be the commutator of T_(Ω)with symbol b∈BMO(R^(n)).In this paper,the authors prove that if sup ζ∈S^(n−1)∫Sn−1^(|Ω(θ)|log^(β)(1/|θ·ζ|)dθ<∞ with β>2,then[b,T_(Ω)]is bounded on Triebel–Lizorkin space F^(0,q)p(R^(n))provided that 1+1/β−1<p,q<β.展开更多
文摘Vessel motions in offshore operations are heavily influenced by uncertain wave loads and hydrodynamic parameters.Yet,traditional deterministic or probabilistic models often fail to capture epistemic ambiguity when data are scarce.We introduce a fuzzy–set framework usingα-cut interval analysis to represent imprecise wave heights,periods,added mass,damping,and stiffness as fuzzy numbers.These are incorporated into the multi-body equations of motion and solved via a fuzzy Runge–Kutta scheme across nestedα-levels.A simulation architecture iterates overα-cuts and time-steps to produce interval bounds on heavy responses.A case study off the Karnataka coast,with realistic sea-state data for moderate and severe scenarios,yields heave-amplitude envelopes whose widths quantify response uncertainty.At mid-confidence(α=0.5),moderate seas produce amplitudes of 8.30–9.65 m(±15%),while severe seas yield 7.15–8.90 m(±22%).Envelope narrowing asα→1 confirms that increased parameter confidence reduces prediction spread,and bias analysis against crisp baselines highlights the impact of imprecision on mean responses.This non-probabilistic approach provides interpretable,worst-and best-case motion bounds without requiring large datasets,offering marine engineers robust safety margins and guidance for targeted data collection and real-time uncertainty updating.
基金Supported by the National Natural Science Foundation of China(11361047)Fundamental Research Program of Shanxi Province(20210302124529)。
文摘This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theorem,fixed point index theory and the analytic technique,we give the bifurcation point of the parameter which divides the range of parameter for the existence of at least two,one and no positive solutions for the problem.And,by using a fixed point theorem of generalized concave operator and cone theory,we establish the maximum parameter interval for the existence of the unique positive solution for the problem and show that such a positive solution continuously depends on the parameter.In the end,some examples are given to illustrate our main results.
文摘Composite resin restorations are routinely exposed to acidic and chromogenic beverages that may alter their surface integrity over time.This in-vitro study evaluated the surface roughness behavior of two universal single-shade(Unishade)composites and two conventionalmulti-shade composites following immersion in commonly consumed staining solutions and assessed whether repolishing could restore smoothness after degradation.A total of 120 standardized disc specimens were fabricated and allocated to fourmaterial groups,with each group subdivided into distilled water,cola,and coffee immersion subgroups.Surface roughness was recorded at baseline,after one week,after one month,and following a final repolishing step using a standardized multi-step system.The findings demonstrated that Unishade composites exhibited more stable surface characteristics across all immersion periods,with changes consistently remaining below the threshold associated with biofilm accumulation.Conventional composites showed greater variability,particularly in cola,where roughness values increased significantly compared with distilled water and coffee.Repolishing substantially reduced immersion-induced roughness in all materials,although its effectiveness varied depending on composite formulation and beverage acidity.Cola produced the greatest surface alterations across all groups,highlighting the erosive potential of low-pH beverages.These results indicate that Unishade composites possess superior resistance to surface degradation,likely due to their nano-structured filler configuration and less hydrophilic resin matrices,while conventional materials appear more susceptible to acidic challenge.Within the limitations of this study,selecting surface-stable material types and applying appropriate finishing and repolishing protocols may enhance the long-term performance and esthetics of composite restorations.
基金supported by the National Natural Science Foundation of China(No.11972357)。
文摘Crossflow instability will be present when the vehicle has an angle of attack in hypersonic flow,and it might play a dominant role in hypersonic boundary layer transition.By far the mechanism of crossflow instability-induced hypersonic boundary layer transition is still out of understanding,although the large effort has been devoted.Upon this work,the overall roughness effect on instabilities in hypersonic flow was researched experimentally.Surface flush-mounted pressure sensors and infrared camera were employed to investigate the instability waves when different rough surfaces were deployed.The results reveal that the moderate surface roughness level on cone model can suppress the growth of crossflow instabilities at certain azimuthal angles in hypersonic flow.
基金supported by the National Natural Science Foundation of China(Grant No.52402430,52572380)the Natural Science Foundation of Shanghai(Grant No.23ZR1466300).
文摘Runway surface roughness significantly influences aircraft vibrations during takeoff and landing,affecting both flight safety and pavement durability.Aircraft operate at high speeds and wide gear spans,making them sensitive to long-wavelength(15–120 m)and lateral irregularities,which are often overlooked in traditional roughness models.This study aims to construct a three-dimensional runway roughness modeling framework integrating"precise detection-spectrum analysis-spatial reconstruction"in response to this issue.Combining the elevation data of 37 runways(5 asphalt runways and 32 cement runways)measured by a vehicle-mounted laser profilometer and the BeiDou positioning system,the power spectrum analysis was carried out by the Burg method and the spectrum models of asphalt and cement runways were fitted respectively.Meanwhile,a new exponential lateral coherence function was proposed.Finally,the three-dimensional spatial model was reconstructed by using the transfer function and genetic algorithm.The results show that the error of the measured elevation data is less than 1 cm.The spectral characteristics of different pavement types are significantly different.Among them,the R^(2) of the asphalt runway fitted with the Sussman model is greater than 0.9.The cement runway needs to be characterized by a piecewise function to represent the spectral mutation.The fitting error of the new index's lateral coherence function has been reduced to 0.012.The reconstructed three-dimensional model is in good agreement with the theoretical value and the error does not exceed 0.18 mm^(2) m/c.Finally,a three-dimensional model of 0–20 m in the lateral direction and 3000 m in the longitudinal direction is generated,providing support for aircraft vibration simulation and pavement maintenance.
基金supported by the National Natural Science Foundation of China (Nos.42422705,42207175,42177117 and 42577170)the Ningbo Youth Leading Talent Project (No.2024QL051)+1 种基金the Chinese Academy of Engineering Science and Technology Strategy Consulting Project (No.2025-XZ-57)the Central Government Funding Program for Guiding Local Science and Technology Development (No.2025ZY01028)。
文摘Rock mass stability is significantly influenced by the heterogeneity of rock joint roughness and shear strength.While modern technology facilitates assessing roughness heterogeneity,evaluating shear strength heterogeneity remains challenging.To address this,this study first captures the morphology of large-scale(1000 mm × 1000 mm) slate and granite joints via 3D laser scanning.Analysis of these surfaces and corresponding push/pull tests on carved specimens revealed a potential correlation between the heterogeneity of roughness and shear strength.A comparative evaluation of five statistical metrics identified information entropy(Hs) as the most robust indicator for quantifying rock joint heterogeneity.Further analysis using Hsreveals that the heterogeneity is anisotropic and,critically,that shear strength heterogeneity is governed not only by roughness heterogeneity but is also significantly influenced by the mean roughness value,normal stress,and intact rock tensile strength.Consequently,a simple comparison of roughness Hsvalues is insufficient for reliably comparing shear strength heterogeneity.To overcome this limitation,a theoretical framework is developed to explicitly map fundamental roughness statistics(mean and heterogeneity) to shear strength heterogeneity.This framework culminates in a practical workflow that allows for the rapid,field-based assessment of shear strength heterogeneity using readily obtainable rock joint roughness data.
基金National Social Science Fund of China,No.24BTJ037Significant Project of the National Social Science Foundation of China,No.23&ZD102+1 种基金The Key Research Base for Philosophy and Social Sciences in Hangzhou:ESG and Sustainable Development Research Center,No.25JD053Zhejiang Provincial Statistical Scientific Research Project,No.25TJZZ12。
文摘Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competitiveness of China’s marine science sector.However,research on the competitiveness of RMIE is limited.To this end,this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of RMIE in China from 2008 to 2020.The findings indicate generally fluctuating upward trends in RMIE’s competitiveness,with Shandong,Jiangsu,and Guangdong showing relatively strong positions.Notably,there are significant intra-regional imbalances and inter-regional asynchrony in RMIE’s competitiveness across China’s three major marine economic circles.Recognizing that forecasting RMIE competitiveness can inform policy formulation,this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects.This model effectively captures the interval and uncertainty characteristics of RMIE’s competitiveness while considering spatial relationships among regions.Results from comparative analysis,robustness tests,and sensitivity analysis demonstrate its superior applicability and forecasting accuracy.Additionally,interval forecasts and scenario analyses suggest that RMIE competitiveness will maintain stable growth,although unbalanced and unsynchronized development is likely to persist.Overall,the approach developed for evaluating and forecasting RMIE competitiveness offers valuable insights for effective policy formulation.
文摘A genetic linkage map with 89 SSR marker loci was constructed based on a maize (Zea mays L.) population consisting of 184 F-2 individuals from the cross, Huangzao 4 X Ye 107. The 184 F-3 families were evaluated in the field under well-watered and drought-stressed regimes in Shanxi Province of China. The objectives of the study were to identify genetic segments responsible for the expression of anthesis-silking interval (ASI), ear setting and grain yield, and to examine if the quantitative trait loci (QTLs) for ASI or yield components can be used in marker-assisted selection (MAS) to improve grain yield under drought conditions. Results showed that under well-watered and drought-stressed regimes, three and two QTLs involved in the expression of ASI were detected on chromosomes 1, 2 and 3, and 2 and 5, respectively. Under well-watered regime, two QTLs for ear setting were detected on chromosomes 3 and 6, explaining about 19.9% of the phenotypic variance, and displayed additive and partial dominant effects, respectively. Under drought-stressed condition, four QTLs for ear setting were detected on chromosomes 3, 7 and 10, which were responsible for interpreting 60.4% of the phenotypic variance, and showed dominant or partial dominant effects. Under well-watered condition, four QTLs controlling grain yield were identified on chromosomes 3, 6 and 7, while five QTLs were identified under drought stress on chromosomes 1, 2, 4 and 8. The gene action was of additive or partial dominant effects, and each QTL could explain 7.3% to 22.0% of the phenotypic variance, respectively. Under drought conditions, ASI and ear setting percentage were highly correlated with grain yield, which can be used as secondary traits for grain yield selection. Based on linked markers detected and gene action analyzed, an MAS strategy for yield improvement under drought condition could be established, which consists of QTLs contributing to decreased ASI and to increased ear setting and grain yield, respectively.
文摘A field study was conducted on the experimental farm of ministry of agriculture, located at Palestine Technical University-Kadoorie, to investigate the effects of saline water irrigation through three irrigation intervals on yield of tomato crop and soil properties. The land was prepared and divided into 12 treatments, each of 48 square meters on the first of April. Tomato seedlings were planted on 25 April 2010;the seedlings were irrigated with fresh water for a period of 10 days after planting. Three levels of saline water irrigation (3, 5, 7 dS/m) plus fresh water as control were applied during the growing season. The four irrigation water treatments were applied through three irrigation intervals (every day, every second day and every three days). Gravimetric soil moisture content and soil electrical conductivity were monitored every two weeks during the growing period. Yield measurements were taken for total fruit yield, marketable yield as a percent of total yield, and average fruit weight of each treatment. Results of this study indicated that, plant treatments irrigated with saline water gave the highest yield for treatments irrigated every day compared to the treatments irrigated every second day and every three days. Statistical analysis showed significant differences in yield reduction between every second day and every three days irrigation intervals under 5 and 7 dS/m saline irrigation levels, while there was no significant difference between irrigation intervals under 3 dS/m salinity level.
文摘According to the American Heart Association’s (AHA) recent statistical update, over 2150 Americans die each day from cardiovascular disease (CVD), which equals approximately 1 death every 40 seconds;many of which were under the age of 65 years old [1]. In 2009, 386,324 people, 1 in 6 Americans, died as a result of coronary artery disease (CAD) alone [1]. They also estimate 150,000 people have “silent” heart attacks each year [1]. Even though the number of cardiovascular disease deaths has declined in the last 10 years, they still accounted for 32.3% of American deaths [1]. As a result, the AHA updated their 2020 goals to improve the nation’s cardiovascular health by 20% [1]. One of these methods is through the use of cardiac rehabilitation. Cardiac rehabilitation (CR) is a health promotion strategy to help return cardiac patients to their previous level of functioning, increase health, decrease comorbidities and promote education and lifestyle change. For select patients, another alternative exercise plan may exist to gain even better results. High intensity interval training (HIIT) has shown positive training results for athletes and many studies show that it may also be an effective exercise modality for many cardiac patients instead of the traditional circuit training method. This article will review current literature on the effects of HIIT on CR patients as well as a sample HIIT protocol for instituting this treatment with appropriate patients.
基金supported by grants from the National Natural Science Foundation of China(Nos.10971185 and 10971186)the Natural Science Foundation of Fujiang Province in China(No.2008F5066).
文摘This paper combines interval-valued intuitionistic fuzzy sets and rough sets.It studies rougheness in interval-valued intuitionistic fuzzy sets and proposes one kind of interval-valued intuitionistic fuzzy-rough sets models under the equivalence relation in crisp sets.That extends the classical rough set defined by Pawlak.
文摘Fusing the structure feature of interval concept lattice and the actual needs of rough control rules,we have constructed the decision interval concept lattice,further more,we also have built a rules mining model of rough control based on decision interval concept lattice,in order to achieve the optimality between rough control mining cost and control efficiency.Firstly,we have preprocessed the collected original data,so that we can transform it into Boolean formal context form,and then we have constructed the decision interval concept lattice in rough control;secondly,we have established the control rules mining algorithm based on decision interval concept lattice.By analyzing and judging redundant rules,we have formed the rough control association rule base in end.Analysis shows that under the premise of improving the reliability of rules,we have achieved the rough control optimization goal between cost and efficiency.Finally,the model of reservoir scheduling has verified its feasibility and efficiency.
文摘This paper proposes an optimal failure-finding interval （FFI） model based on maximizing expected availability. The model can be viewed as an extension and improvement to the model presented in Moubray （1997）. Numerical results are also included to illustrate the appropriateness of the proposed model.
基金funding from the National Natural Science Foundation of China (Grant No.42277175)the pilot project of cooperation between the Ministry of Natural Resources and Hunan Province“Research and demonstration of key technologies for comprehensive remote sensing identification of geological hazards in typical regions of Hunan Province” (Grant No.2023ZRBSHZ056)the National Key Research and Development Program of China-2023 Key Special Project (Grant No.2023YFC2907400).
文摘Joint roughness coefficient(JRC)is the most commonly used parameter for quantifying surface roughness of rock discontinuities in practice.The system composed of multiple roughness statistical parameters to measure JRC is a nonlinear system with a lot of overlapping information.In this paper,a dataset of eight roughness statistical parameters covering 112 digital joints is established.Then,the principal component analysis method is introduced to extract the significant information,which solves the information overlap problem of roughness characterization.Based on the two principal components of extracted features,the white shark optimizer algorithm was introduced to optimize the extreme gradient boosting model,and a new machine learning(ML)prediction model was established.The prediction accuracy of the new model and the other 17 models was measured using statistical metrics.The results show that the prediction result of the new model is more consistent with the real JRC value,with higher recognition accuracy and generalization ability.
基金funding support from the National Science Fund for Distinguished Young Scholars(Grant No.52125904)the National Key R&D Plan(Grant No.2022YFC3004403)the National Natural Science Foundation of China(Grant No.52039008).
文摘To address prediction errors and limited information extraction in machine learning(ML)-based interval prediction,a hybrid model was proposed for interval estimation and failure assessment of step-like landslides under uncertainty.The model decomposed displacements into trend and periodic components via Variational Mode Decomposition(VMD)and K-shape clustering.The Residual and Moving Block Bootstrap methods were used to generate pseudo datasets.Polynomial regressionwas adopted for trend forecasting,whereas the Dense Convolutional Network(DenseNet)and Long Short-Term Memory(LSTM)networks were employed for periodic displacement prediction.An Extreme Learning Machine(ELM)was used to estimate the noise variance,enabling the construction of Prediction Intervals(PIs)and quantificationof displacement uncertainty.Failure probabilities(Pf)were derived from PIs using an improved tangential angle criterion and reliability analysis.The model was validated on three step-like landslides in the Three Gorges Reservoir Area,achieving stability assessment accuracies of 99.88%(XD01),99.93%(ZG93),99.89%(ZG118),and 100%for ZG110 and ZG111 across the Baishuihe and Bazimen landslides.For the Shuping landslide,the predictions aligned with fieldobservations before and after the 2014–2015 remediation,with P_(f)remaining near zero post-2015 except for occasional peaks.The model outperformed conventional ML approaches by yielding narrower PIs.At XD01 with 90%PI nominal confidencelevel(PINC),the coverage width-based criterion(CWC)and PI average width(PIAW)were 3.38 mm.The mean values of the PIs exhibited high accuracy,with a Mean Absolute Error(MAE)of 0.28 mm and Root Mean Square Error(RMSE)of 0.39 mm.These results demonstrate the robustness of the proposed model in improving landslide risk assessment and decision-making under uncertainty.
基金funding support from the National Natural Science Foundation of China(Grant No.52274082)the Program of Qingjiang Excellent Young Talents,Jiangxi University of Science and Technology(Grant No.JXUSTQJBJ2020003)the Innovation Fund Designated for Graduate Students of Jiangxi Province(Grant No.YC2023-B215).
文摘The roughness of the fracture surface directly affects the strength,deformation,and permeability of the surrounding rock in deep underground engineering.Understanding the effect of high temperature and thermal cycle on the fracture surface roughness plays an important role in estimating the damage degree and stability of deep rock mass.In this paper,the variations of fracture surface roughness of granite after different heating and thermal cycles were investigated using the joint roughness coefficient method(JRC),three-dimensional(3D)roughness parameters,and fractal dimension(D),and the mechanism of damage and deterioration of granite were revealed.The experimental results show an increase in the roughness of the granite fracture surface as temperature and cycle number were incremented.The variations of JRC,height parameter,inclination parameter and area parameter with the temperature conformed to the Boltzmann's functional distribution,while the D decreased linearly as the temperature increased.Besides,the anisotropy index(Ip)of the granite fracture surface increased as the temperature increased,and the larger parameter values of roughness characterization at different temperatures were attained mainly in directions of 20°–40°,60°–100°and 140°–160°.The fracture aperture of granite after fracture followed the Gauss distribution and the average aperture increased with increasing temperature,which increased from 0.665 mm at 25℃to 1.058 mm at 800℃.High temperature caused an uneven thermal expansion,water evaporation,and oxidation of minerals within the granite,which promoted the growth and expansion of microfractures,and reduced interparticle bonding strength.In particular,the damage was exacerbated by the expansion and cracking of the quartz phase transition after T>500℃.Thermal cycles contributed to the accumulation of this damage and further weakened the interparticle bonding forces,resulting in a significant increase in the roughness,anisotropy,and aperture of the fracture surface after five cycles.
基金supported by the National Key Research and Development Program of China(2022YFB3605902)the National Natural Science Foundation of China(52375411,52293402)。
文摘Workpiece rotational grinding is widely used in the ultra-precision machining of hard and brittle semiconductor materials,including single-crystal silicon,silicon carbide,and gallium arsenide.Surface roughness and subsurface damage depth(SDD)are crucial indicators for evaluating the surface quality of these materials after grinding.Existing prediction models lack general applicability and do not accurately account for the complex material behavior under grinding conditions.This paper introduces novel models for predicting both surface roughness and SDD in hard and brittle semiconductor materials.The surface roughness model uniquely incorporates the material’s elastic recovery properties,revealing the significant impact of these properties on prediction accuracy.The SDD model is distinguished by its analysis of the interactions between abrasive grits and the workpiece,as well as the mechanisms governing stress-induced damage evolution.The surface roughness model and SDD model both establish a stable relationship with the grit depth of cut(GDC).Additionally,we have developed an analytical relationship between the GDC and grinding process parameters.This,in turn,enables the establishment of an analytical framework for predicting surface roughness and SDD based on grinding process parameters,which cannot be achieved by previous models.The models were validated through systematic experiments on three different semiconductor materials,demonstrating excellent agreement with experimental data,with prediction errors of 6.3%for surface roughness and6.9%for SDD.Additionally,this study identifies variations in elastic recovery and material plasticity as critical factors influencing surface roughness and SDD across different materials.These findings significantly advance the accuracy of predictive models and broaden their applicability for grinding hard and brittle semiconductor materials.
基金funded by Jilin Province Science and Technology Development Plan Project,grant number 20220203163SF.
文摘With the increasing integration of large-scale distributed energy resources into the grid,traditional distribution network optimization and dispatch methods struggle to address the challenges posed by both generation and load.Accounting for these issues,this paper proposes a multi-timescale coordinated optimization dispatch method for distribution networks.First,the probability box theory was employed to determine the uncertainty intervals of generation and load forecasts,based on which,the requirements for flexibility dispatch and capacity constraints of the grid were calculated and analyzed.Subsequently,a multi-timescale optimization framework was constructed,incorporating the generation and load forecast uncertainties.This framework included optimization models for dayahead scheduling,intra-day optimization,and real-time adjustments,aiming to meet flexibility needs across different timescales and improve the economic efficiency of the grid.Furthermore,an improved soft actor-critic algorithm was introduced to enhance the uncertainty exploration capability.Utilizing a centralized training and decentralized execution framework,a multi-agent SAC network model was developed to improve the decision-making efficiency of the agents.Finally,the effectiveness and superiority of the proposed method were validated using a modified IEEE-33 bus test system.
基金funded by the National Natural Science Foundation Projects(Grant Nos.41772287 and 42277132)the Key R&D Project of Zhejiang Province(Grant No.2021C03159).
文摘The scale effect on shear strength of rock joints is well-documented.However,whether scale effects are negative,positive,or even exist or not is still controversial.Joint roughness significantly influences the shear strength of rock joints.Compared to the shear tests,using the joint roughness coefficient(JRC)and its roughness parameters offers a more convenient method for describing the scale effect on shear strength.However,it is crucial to understand that the scale effect mechanisms of JRC are distinct from those of shear strength.Therefore,this paper aims to clarify these distinct mechanisms.By digitally extracting roughness parameters from granite samples,it is found that the scale effect of roughness parameters mainly comes from the sampling methods and the geometric characteristics of parameters.Furthermore,a full data sampling method considering heterogeneity is proposed to obtain more representative roughness parameters.To reveal the scale effect mechanisms of shear strength,Gaussian filtering is firstly used to separate the waviness and unevenness components of roughness,facilitating a deeper understanding of the geometric characteristics of roughness.It is suggested that the wavelength of the waviness component can reflect the scale effect on shear strength.Secondly,numerical simulations of ideal artificial joint models are conducted to validate that the wavelength of the waviness component serves as the dividing point between positive and negative scale effects.The mechanical mechanisms of positive and negative scale effects are also interpreted.Finally,these mechanisms successfully elucidate the occurrence patterns of the scale effect on natural joint profiles.
基金Supported by NSFC(No.11971295)Guangdong Higher Education Teaching Reform Project(No.2023307)。
文摘Let Ω be homogeneous of degree zero,integrable on S^(n−1) and have mean value zero,T_(Ω) be the homogeneous singular integral operator with kernel Ω(x)/|x|^(n) and[b,T_(Ω)]be the commutator of T_(Ω)with symbol b∈BMO(R^(n)).In this paper,the authors prove that if sup ζ∈S^(n−1)∫Sn−1^(|Ω(θ)|log^(β)(1/|θ·ζ|)dθ<∞ with β>2,then[b,T_(Ω)]is bounded on Triebel–Lizorkin space F^(0,q)p(R^(n))provided that 1+1/β−1<p,q<β.
