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
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
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
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
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
Pavement condition monitoring and its timely maintenance is necessary to ensure the safety and quality of the roadway infrastructure. The International Roughness Index (IRI) is a commonly used measure to quantify road...Pavement condition monitoring and its timely maintenance is necessary to ensure the safety and quality of the roadway infrastructure. The International Roughness Index (IRI) is a commonly used measure to quantify road surface roughness and is a critical input to asset management. In Indiana, the IRI statistic contributes to roughly half of the pavement quality index computation used for asset management. Most agencies inventory IRI once a year, however, pavement conditions vary much more frequently. The objective of this paper is to develop a framework using crowdsourced connected vehicle data to identify and detect temporal changes in IRI. Over 3 billion connected vehicle records in Indiana were analyzed across 30 months between 2022 and 2024 to understand the spatiotemporal variations in roughness. Annual comparisons across all major interstates in Indiana showed the miles of interstates classified as “Good” decreased from 1896 to 1661 miles between 2022 and 2024. The miles of interstate classified as “Needs Maintenance” increased from 82 to 120 miles. A detailed case study showing monthly and daily changes of estimated IRI on I-65 are presented along with supporting dashcam images. Although the crowdsourced IRI estimates are not as robust as traditional specialized pavement profilers, they can be obtained on a monthly, weekly, or even daily basis. The paper concludes by suggesting a combination of frequent crowdsourced IRI and commercially available dashcam imagery of roadway can provide an agile and responsive mechanism for agencies to implement pavement asset management programs that can complement existing annual programs.展开更多
LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional...LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional Calder´on commutator defined by T*_(Ωa)f(x):=sup_(ε>0)|∫_(|x-y|>ε)^Ω(x-y)/|x-y|^(d+1)(a(x)-a(y))f(y)dy.In this paper,the authors establish bilinear sparse domination for T*_(Ω,a) under the assumption Ω∈L∞(Sd−1).As applications,some quantitative weighted bounds for T*_(Ω,a) are obtained.展开更多
Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives ...Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.展开更多
As the dominant seepage channel in rock masses,it is of great significance to study the influence of fracture roughness distribution on seepage and heat transfer in rock masses.In this paper,the fracture roughness dis...As the dominant seepage channel in rock masses,it is of great significance to study the influence of fracture roughness distribution on seepage and heat transfer in rock masses.In this paper,the fracture roughness distribution functions of the Bakhtiary dam site and Oskarshamn/Forsmark mountain were fitted using statistical methods.The COMSOL Multiphysics finite element software was utilized to analyze the effects of fracture roughness distribution types and empirical formulas for fracture hydraulic aperture on the seepage field and temperature field of rock masses.The results show that:(1)The fracture roughness at the Bakhtiary dam site and Oskarshamn/Forsmark mountain follows lognormal and normal distributions,respectively;(2)For rock masses with the same expected value and standard deviation of fracture roughness,the outflow from rock masses with lognormal distribution of fracture roughness is significantly larger than that of rock masses with normal distribution of fracture roughness;(3)The fracture hydraulic aperture,outflow,and cold front distance of the Li and Jiang model are significantly larger than those of the Barton model;(4)The outflow,hydraulic pressure distribution,and temperature distribution of the Barton model are more sensitive to the fracture roughness distribution type than those of the Li and Jiang model.展开更多
BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs...BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs)often overlook age,sex,and demographic variations.Partitioned RIs,while considering these factors,fail to capture the gradual age-related physiological changes.Next-generation RIs offer a solution to this limitation.AIM To investigate age-and sex-specific dynamics of PG and establish next-generation RIs for adults and the elderly in northern China.METHODS After screening,708 healthy individuals were included in this observational study.Serum PG was measured using chemiluminescence immunoassay.Age-and sex-related effects on PG were analyzed with a two-way analysis of variance.RI partitioning was determined by the standard deviation ratio(SDR).Traditional RIs were established using a non-parametric approach.Generalized Additive Models for Location,Scale,and Shape(GAMLSS)modeled age-related trends and continuous reference percentiles for PG I and PG II.Reference limit flagging rates for both RI types were compared.RESULTS PG I and PG II levels were influenced by age(P<0.001)and sex(P<0.001),while PGR remained stable.Age-specific RIs were required for PG I(SDR=0.366)and PG II(SDR=0.424).Partitioned RIs were established for PG I and PG II,with a single RI for PGR.GAMLSS modeling revealed distinct age-dependent trajectories:PG I increased from a median of 39.75μg/L at age 20 years to 49.75μg/L at age 60 years,a 25.16%increase,after which it plateaued through age 80 years.In contrast,PG II showed a continuous rise throughout the age range,with the median value increasing from 5.07μg/L at age 20 years to 8.36μg/L at age 80 years,corresponding to a 64.89%increase.Continuous reference percentiles intuitively reflected these trends and were detailed in this study.Next-generation RIs demonstrated superior accuracy compared to partitioned RIs when applied to specific age subgroups.CONCLUSION This study elucidates the age-and sex-specific dynamics of PG and,to our knowledge,is the first to establish next-generation RIs for PG,supporting more individualized interpretation in laboratory medicine.展开更多
The distribution of Seidel eigenvalues of cographs is investigated in this paper.We prove that there is no Seidel eigenvalue of nontrivial cographs in the interval(−1,1).We also show the optimality of the interval(−1,...The distribution of Seidel eigenvalues of cographs is investigated in this paper.We prove that there is no Seidel eigenvalue of nontrivial cographs in the interval(−1,1).We also show the optimality of the interval(−1,1)in the sense that for any ε>0 either of the intervals(1,1+ε)and(−1−ε,−1)contains a Seidel eigenvalue of some cograph of order n when n is sufficiently large.展开更多
Objectives:This study aimed to explore the perceptions and recommendations of multiparas and health-related professionals regarding appropriate birth intervals(Bis)and key determinants.Methods:In-depth semi-structured...Objectives:This study aimed to explore the perceptions and recommendations of multiparas and health-related professionals regarding appropriate birth intervals(Bis)and key determinants.Methods:In-depth semi-structured interviews were conducted between April 1 and June 30,2022.Nine multiparas and thirteen health-related professionals were purposefully sampled until data saturation was reached.A thematic analysis approach was applied to the interview transcripts,utilizing dual independent coding and consensus validation in NVivo 12.0.Results:The data generated two overarching categories:1)balanced decision-making on the appropriate birth intervals and 2)internal and external determinants integrated with health and societal considerations.Four key themes emerged following the two categories:1)consistency and discrepancy between the actual and recommended birth intervals of multiparas;2)health-and developmentoriented professional recommendations;3)internal determinants related to individual-level factors;and 4)external determinants related to child-related factors,family support,and social security.Weighing women's reproductive health and career development,multiparas and health-related professionals perceived a length between 18 and 36 months as the appropriate Bl.Conclusion:Multiparas and health-related professionals shaped their balanced recommendations on a relatively appropriate birth interval ranging from 18 to 36 months,which was influenced by women's individual-level factors,child-related factors,family support,and social security.Targeted social and healthcare services should be offered to women and their families during the Bls.展开更多
To tackle the difficulties of the point prediction in quantifying the reliability of landslide displacement prediction,a data-driven combination-interval prediction method(CIPM)based on copula and variational-mode-dec...To tackle the difficulties of the point prediction in quantifying the reliability of landslide displacement prediction,a data-driven combination-interval prediction method(CIPM)based on copula and variational-mode-decomposition associated with kernel-based-extreme-learningmachine optimized by the whale optimization algorithm(VMD-WOA-KELM)is proposed in this paper.Firstly,the displacement is decomposed by VMD to three IMF components and a residual component of different fluctuation characteristics.The key impact factors of each IMF component are selected according to Copula model,and the corresponding WOA-KELM is established to conduct point prediction.Subsequently,the parametric method(PM)and non-parametric method(NPM)are used to estimate the prediction error probability density distribution(PDF)of each component,whose prediction interval(PI)under the 95%confidence level is also obtained.By means of the differential evolution algorithm(DE),a weighted combination model based on the PIs is built to construct the combination-interval(CI).Finally,the CIs of each component are added to generate the total PI.A comparative case study shows that the CIPM performs better in constructing landslide displacement PI with high performance.展开更多
Climate warming is reshaping the phenology of plants in recent decades,with potential implications for forest productivity,carbon sequestration,and ecosystem functioning.While the effects of warming on secondary growt...Climate warming is reshaping the phenology of plants in recent decades,with potential implications for forest productivity,carbon sequestration,and ecosystem functioning.While the effects of warming on secondary growth phenology is becoming increasingly clear,the influenceof environmental factors on different developmental phases of xylem remains to be quantified.In this study,we investigated the temporal dynamics of xylem cell enlargement,wall-thickening,and the interval between these events in twelve temperate tree species from Northeast China over the period 2019–2024.We found that both cell enlargement and wall-thickening advanced significantlyin response to climate warming,with species-specific variations in the rate of advancement.Importantly,the advancing rate of wallthickening was greater than that of cell enlargement,leading to a shortening of the interval between these two events.Linear mixed-effects models revealed that photoperiod,forcing temperature,and precipitation were the primary environmental drivers influencingthe timing of both cell enlargement and wall-thickening,with photoperiod emerging as the most important factor.These results suggest that climate warming accelerates the heat accumulation required for the transition from xylem cell enlargement to wall-thickening,thereby shortening the time interval between these two developmental stages.Beyond contributing valuable multi-year xylem phenological data,our results provide mechanistic insights that enhance predictions of wood formation dynamics under future climate scenarios and improve the accuracy of forest carbon models.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.
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 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.
文摘Pavement condition monitoring and its timely maintenance is necessary to ensure the safety and quality of the roadway infrastructure. The International Roughness Index (IRI) is a commonly used measure to quantify road surface roughness and is a critical input to asset management. In Indiana, the IRI statistic contributes to roughly half of the pavement quality index computation used for asset management. Most agencies inventory IRI once a year, however, pavement conditions vary much more frequently. The objective of this paper is to develop a framework using crowdsourced connected vehicle data to identify and detect temporal changes in IRI. Over 3 billion connected vehicle records in Indiana were analyzed across 30 months between 2022 and 2024 to understand the spatiotemporal variations in roughness. Annual comparisons across all major interstates in Indiana showed the miles of interstates classified as “Good” decreased from 1896 to 1661 miles between 2022 and 2024. The miles of interstate classified as “Needs Maintenance” increased from 82 to 120 miles. A detailed case study showing monthly and daily changes of estimated IRI on I-65 are presented along with supporting dashcam images. Although the crowdsourced IRI estimates are not as robust as traditional specialized pavement profilers, they can be obtained on a monthly, weekly, or even daily basis. The paper concludes by suggesting a combination of frequent crowdsourced IRI and commercially available dashcam imagery of roadway can provide an agile and responsive mechanism for agencies to implement pavement asset management programs that can complement existing annual programs.
文摘LetΩbe homogeneous of degree zero,integrable on S^(d−1) and have vanishing moment of order one,a be a function on R^(d) such that ∇a∈L^(∞)(R^(d)).Let T*_(Ω,a) be the maximaloperator associated with the d-dimensional Calder´on commutator defined by T*_(Ωa)f(x):=sup_(ε>0)|∫_(|x-y|>ε)^Ω(x-y)/|x-y|^(d+1)(a(x)-a(y))f(y)dy.In this paper,the authors establish bilinear sparse domination for T*_(Ω,a) under the assumption Ω∈L∞(Sd−1).As applications,some quantitative weighted bounds for T*_(Ω,a) are obtained.
基金supported by the National Natural Science Foundation of China,Nos.82071426,81873784Clinical Cohort Construction Program of Peking University Third Hospital,No.BYSYDL2019002(all to DF)。
文摘Amyotrophic lateral sclerosis is a rare neurodegenerative disease characterized by the involvement of both upper and lower motor neurons.Early bilateral limb involvement significantly affects patients'daily lives and may lead them to be confined to bed.However,the effect of upper and lower motor neuron impairment and other risk factors on bilateral limb involvement is unclear.To address this issue,we retrospectively collected data from 586 amyotrophic lateral sclerosis patients with limb onset diagnosed at Peking University Third Hospital between January 2020 and May 2022.A univariate analysis revealed no significant differences in the time intervals of spread in different directions between individuals with upper motor neuron-dominant amyotrophic lateral sclerosis and those with classic amyotrophic lateral sclerosis.We used causal directed acyclic graphs for risk factor determination and Cox proportional hazards models to investigate the association between the duration of bilateral limb involvement and clinical baseline characteristics in amyotrophic lateral sclerosis patients.Multiple factor analyses revealed that higher upper motor neuron scores(hazard ratio[HR]=1.05,95%confidence interval[CI]=1.01–1.09,P=0.018),onset in the left limb(HR=0.72,95%CI=0.58–0.89,P=0.002),and a horizontal pattern of progression(HR=0.46,95%CI=0.37–0.58,P<0.001)were risk factors for a shorter interval until bilateral limb involvement.The results demonstrated that a greater degree of upper motor neuron involvement might cause contralateral limb involvement to progress more quickly in limb-onset amyotrophic lateral sclerosis patients.These findings may improve the management of amyotrophic lateral sclerosis patients with limb onset and the prediction of patient prognosis.
基金College Students Innovation and Entrepreneurship Project of Guangzhou Railway Polytechnic(2025CXCY015)。
文摘As the dominant seepage channel in rock masses,it is of great significance to study the influence of fracture roughness distribution on seepage and heat transfer in rock masses.In this paper,the fracture roughness distribution functions of the Bakhtiary dam site and Oskarshamn/Forsmark mountain were fitted using statistical methods.The COMSOL Multiphysics finite element software was utilized to analyze the effects of fracture roughness distribution types and empirical formulas for fracture hydraulic aperture on the seepage field and temperature field of rock masses.The results show that:(1)The fracture roughness at the Bakhtiary dam site and Oskarshamn/Forsmark mountain follows lognormal and normal distributions,respectively;(2)For rock masses with the same expected value and standard deviation of fracture roughness,the outflow from rock masses with lognormal distribution of fracture roughness is significantly larger than that of rock masses with normal distribution of fracture roughness;(3)The fracture hydraulic aperture,outflow,and cold front distance of the Li and Jiang model are significantly larger than those of the Barton model;(4)The outflow,hydraulic pressure distribution,and temperature distribution of the Barton model are more sensitive to the fracture roughness distribution type than those of the Li and Jiang model.
文摘BACKGROUND Pepsinogen(PG)and the PG I/II ratio(PGR)are critical indicators for diagnosing Helicobacter pylori infection and chronic atrophic gastritis,and assessing gastric cancer risk.Existing reference intervals(RIs)often overlook age,sex,and demographic variations.Partitioned RIs,while considering these factors,fail to capture the gradual age-related physiological changes.Next-generation RIs offer a solution to this limitation.AIM To investigate age-and sex-specific dynamics of PG and establish next-generation RIs for adults and the elderly in northern China.METHODS After screening,708 healthy individuals were included in this observational study.Serum PG was measured using chemiluminescence immunoassay.Age-and sex-related effects on PG were analyzed with a two-way analysis of variance.RI partitioning was determined by the standard deviation ratio(SDR).Traditional RIs were established using a non-parametric approach.Generalized Additive Models for Location,Scale,and Shape(GAMLSS)modeled age-related trends and continuous reference percentiles for PG I and PG II.Reference limit flagging rates for both RI types were compared.RESULTS PG I and PG II levels were influenced by age(P<0.001)and sex(P<0.001),while PGR remained stable.Age-specific RIs were required for PG I(SDR=0.366)and PG II(SDR=0.424).Partitioned RIs were established for PG I and PG II,with a single RI for PGR.GAMLSS modeling revealed distinct age-dependent trajectories:PG I increased from a median of 39.75μg/L at age 20 years to 49.75μg/L at age 60 years,a 25.16%increase,after which it plateaued through age 80 years.In contrast,PG II showed a continuous rise throughout the age range,with the median value increasing from 5.07μg/L at age 20 years to 8.36μg/L at age 80 years,corresponding to a 64.89%increase.Continuous reference percentiles intuitively reflected these trends and were detailed in this study.Next-generation RIs demonstrated superior accuracy compared to partitioned RIs when applied to specific age subgroups.CONCLUSION This study elucidates the age-and sex-specific dynamics of PG and,to our knowledge,is the first to establish next-generation RIs for PG,supporting more individualized interpretation in laboratory medicine.
基金Supported by the National Natural Science Foundation of China(Grant No.12001006)the Natural Science Foundation of Universities of Anhui Province(Grant No.2023AH050904).
文摘The distribution of Seidel eigenvalues of cographs is investigated in this paper.We prove that there is no Seidel eigenvalue of nontrivial cographs in the interval(−1,1).We also show the optimality of the interval(−1,1)in the sense that for any ε>0 either of the intervals(1,1+ε)and(−1−ε,−1)contains a Seidel eigenvalue of some cograph of order n when n is sufficiently large.
基金supported by the Key Discipline Program of the Fifth Round of the Three-Year Public Health Action Plan(2020-2022 Year)of Shanghai,China(GWV-10.1-XK08).
文摘Objectives:This study aimed to explore the perceptions and recommendations of multiparas and health-related professionals regarding appropriate birth intervals(Bis)and key determinants.Methods:In-depth semi-structured interviews were conducted between April 1 and June 30,2022.Nine multiparas and thirteen health-related professionals were purposefully sampled until data saturation was reached.A thematic analysis approach was applied to the interview transcripts,utilizing dual independent coding and consensus validation in NVivo 12.0.Results:The data generated two overarching categories:1)balanced decision-making on the appropriate birth intervals and 2)internal and external determinants integrated with health and societal considerations.Four key themes emerged following the two categories:1)consistency and discrepancy between the actual and recommended birth intervals of multiparas;2)health-and developmentoriented professional recommendations;3)internal determinants related to individual-level factors;and 4)external determinants related to child-related factors,family support,and social security.Weighing women's reproductive health and career development,multiparas and health-related professionals perceived a length between 18 and 36 months as the appropriate Bl.Conclusion:Multiparas and health-related professionals shaped their balanced recommendations on a relatively appropriate birth interval ranging from 18 to 36 months,which was influenced by women's individual-level factors,child-related factors,family support,and social security.Targeted social and healthcare services should be offered to women and their families during the Bls.
基金financially supported by the National Natural Science Foundation of China(Nos.42277149,41502299,41372306)the Research Planning of Sichuan Education Department,China(No.16ZB0105)+3 种基金the State Key Laboratory of Geohazard Prevention and Geoenvironment Protection Independent Research Project(Nos.SKLGP2016Z007,SKLGP2018Z017,SKLGP2020Z009)Chengdu University of Technology Young and Middle Aged Backbone Program(No.KYGG201720)Sichuan Provincial Science and Technology Department Program(No.19YYJC2087)China Scholarship Council。
文摘To tackle the difficulties of the point prediction in quantifying the reliability of landslide displacement prediction,a data-driven combination-interval prediction method(CIPM)based on copula and variational-mode-decomposition associated with kernel-based-extreme-learningmachine optimized by the whale optimization algorithm(VMD-WOA-KELM)is proposed in this paper.Firstly,the displacement is decomposed by VMD to three IMF components and a residual component of different fluctuation characteristics.The key impact factors of each IMF component are selected according to Copula model,and the corresponding WOA-KELM is established to conduct point prediction.Subsequently,the parametric method(PM)and non-parametric method(NPM)are used to estimate the prediction error probability density distribution(PDF)of each component,whose prediction interval(PI)under the 95%confidence level is also obtained.By means of the differential evolution algorithm(DE),a weighted combination model based on the PIs is built to construct the combination-interval(CI).Finally,the CIs of each component are added to generate the total PI.A comparative case study shows that the CIPM performs better in constructing landslide displacement PI with high performance.
基金supported by the Ministry of Science and Technology(No:2019FY101602).
文摘Climate warming is reshaping the phenology of plants in recent decades,with potential implications for forest productivity,carbon sequestration,and ecosystem functioning.While the effects of warming on secondary growth phenology is becoming increasingly clear,the influenceof environmental factors on different developmental phases of xylem remains to be quantified.In this study,we investigated the temporal dynamics of xylem cell enlargement,wall-thickening,and the interval between these events in twelve temperate tree species from Northeast China over the period 2019–2024.We found that both cell enlargement and wall-thickening advanced significantlyin response to climate warming,with species-specific variations in the rate of advancement.Importantly,the advancing rate of wallthickening was greater than that of cell enlargement,leading to a shortening of the interval between these two events.Linear mixed-effects models revealed that photoperiod,forcing temperature,and precipitation were the primary environmental drivers influencingthe timing of both cell enlargement and wall-thickening,with photoperiod emerging as the most important factor.These results suggest that climate warming accelerates the heat accumulation required for the transition from xylem cell enlargement to wall-thickening,thereby shortening the time interval between these two developmental stages.Beyond contributing valuable multi-year xylem phenological data,our results provide mechanistic insights that enhance predictions of wood formation dynamics under future climate scenarios and improve the accuracy of forest carbon models.
