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
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
BACKGROUND Meniscal tears are one of the most common knee injuries.After the diagnosis of a meniscal tear has been made,there are several factors physicians use to guide clinical decision-making.The influence of time ...BACKGROUND Meniscal tears are one of the most common knee injuries.After the diagnosis of a meniscal tear has been made,there are several factors physicians use to guide clinical decision-making.The influence of time between injury and isolated meniscus repair on patient outcomes is not well described.Assessing this relationship is important as it may influence clinical decision-making and can add to the preoperative patient education process.We hypothesized that increasing the time from injury to meniscus surgery would worsen postoperative outcomes.AIM To investigate the current literature for data on the relationship between time between meniscus injury and repair on patient outcomes.METHODS PubMed,Academic Search Complete,MEDLINE,CINAHL,and SPORTDiscus were searched for studies published between January 1,1995 and July 13,2023 on isolated meniscus repair.Exclusion criteria included concomitant ligament surgery,incomplete outcomes or time to surgery data,and meniscectomies.Patient demographics,time to injury,and postoperative outcomes from each study were abstracted and analyzed.RESULTS Five studies met all inclusion and exclusion criteria.There were 204(121 male,83 female)patients included.Three of five(60%)studies determined that time between injury and surgery was not statistically significant for postoperative Lysholm scores(P=0.62),Tegner scores(P=0.46),failure rate(P=0.45,P=0.86),and International Knee Documentation Committee scores(P=0.65).Two of five(40%)studies found a statistically significant increase in Lysholm scores with shorter time to surgery(P=0.03)and a statistically significant association between progression of medial meniscus extrusion ratio(P=0.01)and increasing time to surgery.CONCLUSION Our results do not support the hypothesis that increased time from injury to isolated meniscus surgery worsens postoperative outcomes.Decision-making primarily based on injury interval is thus not recommended.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
This study investigates the application of large language models in analyzing sentiment features within the exchange rate markets.Traditional natural language processing methods,such as LDA and BERT,are effective in e...This study investigates the application of large language models in analyzing sentiment features within the exchange rate markets.Traditional natural language processing methods,such as LDA and BERT,are effective in extracting topics from text;however,they fail to assess the relative importance of these topics in relation to target exchange rates.To bridge this gap,this paper employs ChatGPT to extract topics from texts and evaluate their importance scores,further enhancing exchange rate forecasting by integrating topic importance into the sentiment analysis framework.Through empirical analysis,the superiority of ChatGPT over LDA and BERT in both topic extraction and importance assessment is demonstrated.Furthermore,this study utilizes the topic importance scores generated by ChatGPT to develop a novel interval-valued sentiment index(TIS index).This index not only accounts for the relative importance of various events influencing exchange rate fluctuations but also captures the dynamic evolution of market sentiment within an interval.Empirical results highlight that the TIS Index significantly enhances the forecasting accuracy of interval models such as TARI and IMLP for exchange rates.These findings further demonstrate the advantages of ChatGPT in sentiment analysis within the foreign exchange market.These findings offer new insights into the application of ChatGPT in financial text research.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
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
This paper presents the dynamical properties of a discrete-time prey-predator model with refuge in prey under imprecise biological parameters.We consider the refuge concept of prey,which is proportional to the density...This paper presents the dynamical properties of a discrete-time prey-predator model with refuge in prey under imprecise biological parameters.We consider the refuge concept of prey,which is proportional to the density of prey species with interval parameters.The model develops with natural interval parameters since the uncertainties of parameters of any ecological system are a widespread phenomenon in nature.The equilibria of the model are obtained,and the dynamic behaviours of the proposed system are examined.Simulations of the model are performed for different parameters of the model.Numerical simulations show that the proposed discrete model exhibits rich dynamics of a chaotic and complex nature.Our study,through analytical derivation and numerical example,presents the effect of refuge on population dynamics under imprecise biological parameters.展开更多
Wind turbines are continuously exposed to harsh environmental and operational conditions throughout their lifetime,leading to the gradual degradation of their components.If left unaddressed,these degraded components c...Wind turbines are continuously exposed to harsh environmental and operational conditions throughout their lifetime,leading to the gradual degradation of their components.If left unaddressed,these degraded components can adversely affect turbine performance and significantly increase the likelihood of failure.As degradation progresses,the risk of failure escalates,making it essential to implement appropriate risk control measures.One effective risk control method involves performing inspection and monitoring activities that provide valuable insights into the condition of the structure,enabling the formulation of appropriate maintenance strategies based on accurate assessments.Supervisory Control and Data Acquisition(SCADA)systems offer low-resolution condition monitoring data that can be used for fault detection,diagnosis,quantification,prognosis,and maintenance planning.One commonly used method involves predicting power generation using SCADA data and comparing it against measured power generation.Significant discrepancies between predicted and measured values can indicate suboptimal operation,natural aging,or unnatural faults.Various predictive models,including parametric and non-parametric(statistical)approaches,have been proposed for estimating power generation.However,the imperfect nature of these models introduces uncertainties in the predicted power output.Additionally,SCADA monitoring data is prone to uncertainties arising from various sources.The presence of uncertainties from these two sources-imperfect predictive models and imperfect SCADA data-introduces uncertainty in the predicted power generation.This uncertainty complicates the process of determining whether discrepancies between measured and predicted values are significant enough to warrant maintenance actions.Depending on the nature of uncertainty-aleatory,arising from inherent randomness,or epistemic,stemming from incomplete knowledge or limited data-different analytical approaches,like Probabilistic and Possibilistic,can be applied for effective management.Both,Probabilistic and Possibilistic,Approaches offer distinct advantages and limitations.The Possibilistic Approach,rooted in fuzzy set theory,is particularly well suited for addressing epistemic uncertainties,especially those caused by imprecision or sparse statistical information.This makes it especially relevant for applications such as wind turbines,where it is often challenging to construct accurate probability distribution functions for environmental parameters due to limited sensor data from hard-to-access locations.This research focuses on developing a methodology for identifying suboptimal operation in wind turbines by comparing Grid Produced Power(Measured Produced Power)with Predicted Produced Power.To achieve this,the paper introduces a Possibilistic Approach for power prediction that accounts for uncertainties stemming from both model imperfections and measurement errors in SCADA data.The methodology combines machine learning models,used to establish predictive relationships between environmental inputs and power output,with a Possibilistic Framework that represents uncertainty through possibility distribution functions based on fuzzy logic and interval analysis.A real-world case study using operational SCADA data demonstrates the approach,with XGBoost selected as the final predictive model due to its strong accuracy and computational efficiency.展开更多
Seepage refers to the flow of water through porous materials.This phenomenon has a crucial role in dam,slope,excavation,tunnel,and well design.Performing seepage analysis usually is a challenging task,as one must cope...Seepage refers to the flow of water through porous materials.This phenomenon has a crucial role in dam,slope,excavation,tunnel,and well design.Performing seepage analysis usually is a challenging task,as one must cope with the uncertainty associated with the parameters such as the hydraulic conductivity in the horizontal and vertical directions that drive this phenomenon.However,at the same time,the data on horizontal and vertical hydraulic conductivities are typically scarce in spatial resolution.In this context,so-called non-traditional approaches for uncertainty quantification(such as intervals and fuzzy variables)offer an interesting alternative to classical probabilistic methods,since they have been shown to be quite effective when limited information on the governing parameters of a phenomenon is available.Therefore,the main contribution of this study is the development of a framework for conducting seepage analysis in saturated soils,where uncertainty associated with hydraulic conductivity is characterized using fuzzy fields.This method to characterize uncertainty extends interval fields towards the domain of fuzzy numbers.In fact,it is illustrated that fuzzy fields are an effective tool for capturing uncertainties with a spatial component,since they allow one to account for available physical measurements.A case study in confined saturated soil shows that with the proposed framework,it is possible to quantify the uncertainty associated with seepage flow,exit gradient,and uplift force effectively.展开更多
The Palu segment,situated in the northeastern part of the East Anatolian Fault System(EAFS),is a crucial structural feature with notable seismic potential.This study examines the paleoseismic activity of the Palu segm...The Palu segment,situated in the northeastern part of the East Anatolian Fault System(EAFS),is a crucial structural feature with notable seismic potential.This study examines the paleoseismic activity of the Palu segment through trench excavations and geochronological analyses utilizing Optically Stimulated Luminescence(OSL)and radiocarbon(14C)dating methods.Two trenches,located near Karşıbahçeler,exposed evidence of multiple surface-rupturing seismic events spanning the Holocene and Pleistocene epochs.Chronological analyses identified five distinct seismic events in trench 1(P1),dated between 94.09±6.07 ka and 0.84±0.45 ka,and three events in trench 2(P2),dated between 28.83±1.61 ka and 351±21 BP.Bayesian analysis using Oxcal distribution suggested event timings between 90.52±25.99 ka and 1.25±0.55 ka.Comparative analysis with historical earthquake records correlates the most recent event with the 1789 or 1874 AD earthquakes,while the penultimate event matches the 995 AD earthquake.Earlier events reflect prehistoric tectonic activity.The recurrence intervals for these events range from 710 to 5,370 years during the Holocene,with evidence of seismic activity extending into the Pleistocene.Stress inversion analyses and geodetic data indicate a predominantly strike-slip stress regime,consistent with geometry of the fault.These findings provide critical insights into the long-term seismic behavior and recurrence patterns of the Palu segment,enhancing seismic hazard assessments for the region.展开更多
Paleoearthquake research represents an essential method for determining recurrence intervals oflarge earthquakes.Reasonable determination of the average recurrence interval and coefficient of variationprovides a cruci...Paleoearthquake research represents an essential method for determining recurrence intervals oflarge earthquakes.Reasonable determination of the average recurrence interval and coefficient of variationprovides a crucial basis for the analysis of the recurrence characteristics of strong earthquakes on intraplatefaults in Chinese mainland.Paleoearthquake data from 145 fault segments of 93 well-studied faults in MainlandChina were collected,organized,and analyzed to discuss the rational estimation of the average recurrenceinterval and coefficient of variation of a strong earthquake occurrence probability model.First,differencesin structural environments were used as a basis to investigate the spatial distribution characteristics of theaverage recurrence intervals of strong earthquakes.The results indicate significant variations in the recurrenceperiods of strong earthquakes in the Sichuan–Yunnan,Xinjiang,North China,and northeastern Qinghai-Tibet Plateau structure zones.The Sichuan–Yunnan structure zone exhibited the shortest average recurrence intervalfor strong earthquakes,which was mainly distributed between 100 and 2000 years,and a relatively high sliprate.The Xinjiang structure zone attained a relatively balanced recurrence interval frequency distribution of1000–4500 years and a moderate slip rate.The North China structure zone showed the lowest slip rate,withthe strong earthquake recurrence interval mainly concentrated between 1000 and 4000 years.The northeastern Qinghai-Tibet Plateau structure zone presented two main frequency peaks in the strong earthquake recurrenceintervals between 1000–3000 years and 3000–5000 years and a relatively high slip rate.The slip rate is a keyfactor influencing the recurrence interval of strong earthquakes,and active faults with high slip rates showshort recurrence intervals.Furthermore,the relationship between fault slip rate,fault type,and the averagerecurrence interval of strong earthquakes was examined.The results indicate a good logarithmic linearrelationship between the fault slip rate and the average recurrence interval of large earthquakes—the higherthe slip rate,the shorter the recurrence interval of strong earthquakes.Fault type also showed a relation to theaverage recurrence interval,with the intervals for various types of active faults gradually increasing in theorder of strike-slip,normal,reverse strike-slip,reverse,and normal strike-slip faults.Second,we calculated theproportions of active faults and various fault types in each structure zone that had a coefficient of variation inrecurrence intervals less than 0.4.The findings reveal that the occurrence of strong earthquakes on most activefaults in Chinese mainland satisfies a quasiperiodic model.The general coefficient of variation across differentstructure zones and fault types ranges between 0.36 and 0.44,which indicates the nonsignificant difference inthe degree of variability in the periodicity of strong earthquake occurrence across various structural zones andfault types.展开更多
BACKGROUND The reference ranges for biochemical parameters can fluctuate due to factors like altitude,age,gender,and socioeconomic conditions.These values are crucial for interpreting laboratory data and guide clinica...BACKGROUND The reference ranges for biochemical parameters can fluctuate due to factors like altitude,age,gender,and socioeconomic conditions.These values are crucial for interpreting laboratory data and guide clinical treatment decisions.Currently,there is no established set of reference intervals for cord blood biochemical parameters of newborns in India,particularly in Mumbai.AIM To create cord blood biochemical parameters reference intervals specifically for Mumbai,India.METHODS A cross-sectional study was conducted in an Indian tertiary care hospital.This study focused on healthy newborns with normal birth weight,born to pregnant mothers without health issues.Cord blood samples,approximately 2-3 mL in volume,were collected from 210 term neonates.These samples were divided into fluoride(glucose)and clot activator(serum)tubes and were subsequently analyzed in the institute's biochemical laboratory.The data obtained from the analysis was then subjected to statistical analysis.The result of the Shapiro-Wilk test suggested non-normality in the data distribution.Consequently,nonparametric statistics were utilized for analysis.The Mann-Whitney U test was utilized to compare parameter distributions among different factors,including the infant’s sex,delivery method,maternal age,and obstetric history.A significance level of P<0.05 was considered to indicate statistical significance.RESULTS The following represent the median figures and central 95 percentile reference intervals for biochemical parameters in umbilical cord blood of newborns:Serum direct bilirubin=(0.1-0.55)mg/dL,indirect bilirubin=(0.64-2.26)mg/dL,total bilirubin=(0.62-3.14)mg/dL,creatinine=(0.27-0.76)mg/dL,sodium=(128.19-143.26)mmol/L,chloride=(100.19-111.68)mmol/L,potassium=(1.62-9.98)mmol/L and plasma glucose=(24.75-94.23)mg/dL.Statistically significant differences were observed in serum sodium,potassium,and plasma glucose levels when comparing delivery modes.CONCLUSION This is the pioneering study in which first time,the biochemical reference intervals in cord blood for newborns are established in western India.The values are applicable for newborns from this area.Larger study throughout the country is required.展开更多
In the present paper,we obtain the converse results of approximation of a newly introduced genuine Bernstein-Durrmeyer operators in movable interval.We also get the moments properties of an auxiliary operator which ha...In the present paper,we obtain the converse results of approximation of a newly introduced genuine Bernstein-Durrmeyer operators in movable interval.We also get the moments properties of an auxiliary operator which has its own independent values.The moments of the auxiliary operators play important roles in establishing the main result(Theorem 4).展开更多
This paper addresses the computational problem of fixed-interval smoothing state estimation in linear time-varying Gaussian stochastic systems.A new fixed-interval Kalman smoothing algorithm is proposed,and the corres...This paper addresses the computational problem of fixed-interval smoothing state estimation in linear time-varying Gaussian stochastic systems.A new fixed-interval Kalman smoothing algorithm is proposed,and the corresponding form of the smoother is derived.The method is able to accommodate situations where process and measurement noises are correlated,a limitation often encountered in conventional approaches.The Kalman smoothing problem discussed in this paper can be reformulated as an equivalent constrained optimization problem,where the solution corresponds to a set of linear equations defined by a specific co-efficient matrix.Through multiple permutations,the co-efficient matrix of linear equations is transformed into a block tridiagonal form,and then both sides of the linear system are multiplied by the inverse of the co-efficient matrix.This approach is based on the transformation of linear systems described in the SPIKE algorithm and is particularly well-suited for large-scale sparse block tridiagonal matrix structures.It enables efficient,parallel,and flexible solutions while maintaining a certain degree of block diagonal dominance.Compared to directly solving block tridiagonal co-efficient matrices,this method demonstrates appreciable advantages in terms of numerical stability and computational efficiency.Consequently,the new smoothing algorithm yields a new smoother that features fewer constraints and broader applicability than traditional methods.The estimates,such as smoothed state,covariance,and cross-covariance,are essential for fields,such as system identification,navigation,guidance,and control.Finally,the effectiveness of the proposed smoothing algorithm and smoother is validated through numerical simulations.展开更多
High-intensity interval training(HIIT),a highly efficient and distinctive exercise format,has sparked growing academic interest in sports performance training.This article synthesizes theoretical and applied evidence ...High-intensity interval training(HIIT),a highly efficient and distinctive exercise format,has sparked growing academic interest in sports performance training.This article synthesizes theoretical and applied evidence to analyze mechanisms of HIIT in neuromuscular activation,hormonal responses,muscle fiber adaptation,and metabolic pathway effects.It focuses on its effectiveness in enhancing explosive power,maximum strength,and strength endurance,while also examining the integration of HIIT with traditional resistance training,periodized programming,and personalized prescription.Scientific implementation of HIIT can effectively diversify or even replace conventional strength training,not only offering positive directional changes for strength development but also introducing innovative approaches to sports performance training practices.展开更多
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 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.
文摘BACKGROUND Meniscal tears are one of the most common knee injuries.After the diagnosis of a meniscal tear has been made,there are several factors physicians use to guide clinical decision-making.The influence of time between injury and isolated meniscus repair on patient outcomes is not well described.Assessing this relationship is important as it may influence clinical decision-making and can add to the preoperative patient education process.We hypothesized that increasing the time from injury to meniscus surgery would worsen postoperative outcomes.AIM To investigate the current literature for data on the relationship between time between meniscus injury and repair on patient outcomes.METHODS PubMed,Academic Search Complete,MEDLINE,CINAHL,and SPORTDiscus were searched for studies published between January 1,1995 and July 13,2023 on isolated meniscus repair.Exclusion criteria included concomitant ligament surgery,incomplete outcomes or time to surgery data,and meniscectomies.Patient demographics,time to injury,and postoperative outcomes from each study were abstracted and analyzed.RESULTS Five studies met all inclusion and exclusion criteria.There were 204(121 male,83 female)patients included.Three of five(60%)studies determined that time between injury and surgery was not statistically significant for postoperative Lysholm scores(P=0.62),Tegner scores(P=0.46),failure rate(P=0.45,P=0.86),and International Knee Documentation Committee scores(P=0.65).Two of five(40%)studies found a statistically significant increase in Lysholm scores with shorter time to surgery(P=0.03)and a statistically significant association between progression of medial meniscus extrusion ratio(P=0.01)and increasing time to surgery.CONCLUSION Our results do not support the hypothesis that increased time from injury to isolated meniscus surgery worsens postoperative outcomes.Decision-making primarily based on injury interval is thus not recommended.
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 National Natural Science Foundation of China under Grants No.72171223,No.71988101the Youth Innovation Promotion Association of the Chinese Academy of Sciences.
文摘This study investigates the application of large language models in analyzing sentiment features within the exchange rate markets.Traditional natural language processing methods,such as LDA and BERT,are effective in extracting topics from text;however,they fail to assess the relative importance of these topics in relation to target exchange rates.To bridge this gap,this paper employs ChatGPT to extract topics from texts and evaluate their importance scores,further enhancing exchange rate forecasting by integrating topic importance into the sentiment analysis framework.Through empirical analysis,the superiority of ChatGPT over LDA and BERT in both topic extraction and importance assessment is demonstrated.Furthermore,this study utilizes the topic importance scores generated by ChatGPT to develop a novel interval-valued sentiment index(TIS index).This index not only accounts for the relative importance of various events influencing exchange rate fluctuations but also captures the dynamic evolution of market sentiment within an interval.Empirical results highlight that the TIS Index significantly enhances the forecasting accuracy of interval models such as TARI and IMLP for exchange rates.These findings further demonstrate the advantages of ChatGPT in sentiment analysis within the foreign exchange market.These findings offer new insights into the application of ChatGPT in financial text research.
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.
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.
文摘This paper presents the dynamical properties of a discrete-time prey-predator model with refuge in prey under imprecise biological parameters.We consider the refuge concept of prey,which is proportional to the density of prey species with interval parameters.The model develops with natural interval parameters since the uncertainties of parameters of any ecological system are a widespread phenomenon in nature.The equilibria of the model are obtained,and the dynamic behaviours of the proposed system are examined.Simulations of the model are performed for different parameters of the model.Numerical simulations show that the proposed discrete model exhibits rich dynamics of a chaotic and complex nature.Our study,through analytical derivation and numerical example,presents the effect of refuge on population dynamics under imprecise biological parameters.
文摘Wind turbines are continuously exposed to harsh environmental and operational conditions throughout their lifetime,leading to the gradual degradation of their components.If left unaddressed,these degraded components can adversely affect turbine performance and significantly increase the likelihood of failure.As degradation progresses,the risk of failure escalates,making it essential to implement appropriate risk control measures.One effective risk control method involves performing inspection and monitoring activities that provide valuable insights into the condition of the structure,enabling the formulation of appropriate maintenance strategies based on accurate assessments.Supervisory Control and Data Acquisition(SCADA)systems offer low-resolution condition monitoring data that can be used for fault detection,diagnosis,quantification,prognosis,and maintenance planning.One commonly used method involves predicting power generation using SCADA data and comparing it against measured power generation.Significant discrepancies between predicted and measured values can indicate suboptimal operation,natural aging,or unnatural faults.Various predictive models,including parametric and non-parametric(statistical)approaches,have been proposed for estimating power generation.However,the imperfect nature of these models introduces uncertainties in the predicted power output.Additionally,SCADA monitoring data is prone to uncertainties arising from various sources.The presence of uncertainties from these two sources-imperfect predictive models and imperfect SCADA data-introduces uncertainty in the predicted power generation.This uncertainty complicates the process of determining whether discrepancies between measured and predicted values are significant enough to warrant maintenance actions.Depending on the nature of uncertainty-aleatory,arising from inherent randomness,or epistemic,stemming from incomplete knowledge or limited data-different analytical approaches,like Probabilistic and Possibilistic,can be applied for effective management.Both,Probabilistic and Possibilistic,Approaches offer distinct advantages and limitations.The Possibilistic Approach,rooted in fuzzy set theory,is particularly well suited for addressing epistemic uncertainties,especially those caused by imprecision or sparse statistical information.This makes it especially relevant for applications such as wind turbines,where it is often challenging to construct accurate probability distribution functions for environmental parameters due to limited sensor data from hard-to-access locations.This research focuses on developing a methodology for identifying suboptimal operation in wind turbines by comparing Grid Produced Power(Measured Produced Power)with Predicted Produced Power.To achieve this,the paper introduces a Possibilistic Approach for power prediction that accounts for uncertainties stemming from both model imperfections and measurement errors in SCADA data.The methodology combines machine learning models,used to establish predictive relationships between environmental inputs and power output,with a Possibilistic Framework that represents uncertainty through possibility distribution functions based on fuzzy logic and interval analysis.A real-world case study using operational SCADA data demonstrates the approach,with XGBoost selected as the final predictive model due to its strong accuracy and computational efficiency.
文摘Seepage refers to the flow of water through porous materials.This phenomenon has a crucial role in dam,slope,excavation,tunnel,and well design.Performing seepage analysis usually is a challenging task,as one must cope with the uncertainty associated with the parameters such as the hydraulic conductivity in the horizontal and vertical directions that drive this phenomenon.However,at the same time,the data on horizontal and vertical hydraulic conductivities are typically scarce in spatial resolution.In this context,so-called non-traditional approaches for uncertainty quantification(such as intervals and fuzzy variables)offer an interesting alternative to classical probabilistic methods,since they have been shown to be quite effective when limited information on the governing parameters of a phenomenon is available.Therefore,the main contribution of this study is the development of a framework for conducting seepage analysis in saturated soils,where uncertainty associated with hydraulic conductivity is characterized using fuzzy fields.This method to characterize uncertainty extends interval fields towards the domain of fuzzy numbers.In fact,it is illustrated that fuzzy fields are an effective tool for capturing uncertainties with a spatial component,since they allow one to account for available physical measurements.A case study in confined saturated soil shows that with the proposed framework,it is possible to quantify the uncertainty associated with seepage flow,exit gradient,and uplift force effectively.
基金partially supported by the Fırat University Scientific Research Project in Elazığ,Türkiye,under Project Number ADEP.23.12.
文摘The Palu segment,situated in the northeastern part of the East Anatolian Fault System(EAFS),is a crucial structural feature with notable seismic potential.This study examines the paleoseismic activity of the Palu segment through trench excavations and geochronological analyses utilizing Optically Stimulated Luminescence(OSL)and radiocarbon(14C)dating methods.Two trenches,located near Karşıbahçeler,exposed evidence of multiple surface-rupturing seismic events spanning the Holocene and Pleistocene epochs.Chronological analyses identified five distinct seismic events in trench 1(P1),dated between 94.09±6.07 ka and 0.84±0.45 ka,and three events in trench 2(P2),dated between 28.83±1.61 ka and 351±21 BP.Bayesian analysis using Oxcal distribution suggested event timings between 90.52±25.99 ka and 1.25±0.55 ka.Comparative analysis with historical earthquake records correlates the most recent event with the 1789 or 1874 AD earthquakes,while the penultimate event matches the 995 AD earthquake.Earlier events reflect prehistoric tectonic activity.The recurrence intervals for these events range from 710 to 5,370 years during the Holocene,with evidence of seismic activity extending into the Pleistocene.Stress inversion analyses and geodetic data indicate a predominantly strike-slip stress regime,consistent with geometry of the fault.These findings provide critical insights into the long-term seismic behavior and recurrence patterns of the Palu segment,enhancing seismic hazard assessments for the region.
基金Funded by the National Key Research and Development Program(2022YFC3003502).
文摘Paleoearthquake research represents an essential method for determining recurrence intervals oflarge earthquakes.Reasonable determination of the average recurrence interval and coefficient of variationprovides a crucial basis for the analysis of the recurrence characteristics of strong earthquakes on intraplatefaults in Chinese mainland.Paleoearthquake data from 145 fault segments of 93 well-studied faults in MainlandChina were collected,organized,and analyzed to discuss the rational estimation of the average recurrenceinterval and coefficient of variation of a strong earthquake occurrence probability model.First,differencesin structural environments were used as a basis to investigate the spatial distribution characteristics of theaverage recurrence intervals of strong earthquakes.The results indicate significant variations in the recurrenceperiods of strong earthquakes in the Sichuan–Yunnan,Xinjiang,North China,and northeastern Qinghai-Tibet Plateau structure zones.The Sichuan–Yunnan structure zone exhibited the shortest average recurrence intervalfor strong earthquakes,which was mainly distributed between 100 and 2000 years,and a relatively high sliprate.The Xinjiang structure zone attained a relatively balanced recurrence interval frequency distribution of1000–4500 years and a moderate slip rate.The North China structure zone showed the lowest slip rate,withthe strong earthquake recurrence interval mainly concentrated between 1000 and 4000 years.The northeastern Qinghai-Tibet Plateau structure zone presented two main frequency peaks in the strong earthquake recurrenceintervals between 1000–3000 years and 3000–5000 years and a relatively high slip rate.The slip rate is a keyfactor influencing the recurrence interval of strong earthquakes,and active faults with high slip rates showshort recurrence intervals.Furthermore,the relationship between fault slip rate,fault type,and the averagerecurrence interval of strong earthquakes was examined.The results indicate a good logarithmic linearrelationship between the fault slip rate and the average recurrence interval of large earthquakes—the higherthe slip rate,the shorter the recurrence interval of strong earthquakes.Fault type also showed a relation to theaverage recurrence interval,with the intervals for various types of active faults gradually increasing in theorder of strike-slip,normal,reverse strike-slip,reverse,and normal strike-slip faults.Second,we calculated theproportions of active faults and various fault types in each structure zone that had a coefficient of variation inrecurrence intervals less than 0.4.The findings reveal that the occurrence of strong earthquakes on most activefaults in Chinese mainland satisfies a quasiperiodic model.The general coefficient of variation across differentstructure zones and fault types ranges between 0.36 and 0.44,which indicates the nonsignificant difference inthe degree of variability in the periodicity of strong earthquake occurrence across various structural zones andfault types.
文摘BACKGROUND The reference ranges for biochemical parameters can fluctuate due to factors like altitude,age,gender,and socioeconomic conditions.These values are crucial for interpreting laboratory data and guide clinical treatment decisions.Currently,there is no established set of reference intervals for cord blood biochemical parameters of newborns in India,particularly in Mumbai.AIM To create cord blood biochemical parameters reference intervals specifically for Mumbai,India.METHODS A cross-sectional study was conducted in an Indian tertiary care hospital.This study focused on healthy newborns with normal birth weight,born to pregnant mothers without health issues.Cord blood samples,approximately 2-3 mL in volume,were collected from 210 term neonates.These samples were divided into fluoride(glucose)and clot activator(serum)tubes and were subsequently analyzed in the institute's biochemical laboratory.The data obtained from the analysis was then subjected to statistical analysis.The result of the Shapiro-Wilk test suggested non-normality in the data distribution.Consequently,nonparametric statistics were utilized for analysis.The Mann-Whitney U test was utilized to compare parameter distributions among different factors,including the infant’s sex,delivery method,maternal age,and obstetric history.A significance level of P<0.05 was considered to indicate statistical significance.RESULTS The following represent the median figures and central 95 percentile reference intervals for biochemical parameters in umbilical cord blood of newborns:Serum direct bilirubin=(0.1-0.55)mg/dL,indirect bilirubin=(0.64-2.26)mg/dL,total bilirubin=(0.62-3.14)mg/dL,creatinine=(0.27-0.76)mg/dL,sodium=(128.19-143.26)mmol/L,chloride=(100.19-111.68)mmol/L,potassium=(1.62-9.98)mmol/L and plasma glucose=(24.75-94.23)mg/dL.Statistically significant differences were observed in serum sodium,potassium,and plasma glucose levels when comparing delivery modes.CONCLUSION This is the pioneering study in which first time,the biochemical reference intervals in cord blood for newborns are established in western India.The values are applicable for newborns from this area.Larger study throughout the country is required.
文摘In the present paper,we obtain the converse results of approximation of a newly introduced genuine Bernstein-Durrmeyer operators in movable interval.We also get the moments properties of an auxiliary operator which has its own independent values.The moments of the auxiliary operators play important roles in establishing the main result(Theorem 4).
文摘This paper addresses the computational problem of fixed-interval smoothing state estimation in linear time-varying Gaussian stochastic systems.A new fixed-interval Kalman smoothing algorithm is proposed,and the corresponding form of the smoother is derived.The method is able to accommodate situations where process and measurement noises are correlated,a limitation often encountered in conventional approaches.The Kalman smoothing problem discussed in this paper can be reformulated as an equivalent constrained optimization problem,where the solution corresponds to a set of linear equations defined by a specific co-efficient matrix.Through multiple permutations,the co-efficient matrix of linear equations is transformed into a block tridiagonal form,and then both sides of the linear system are multiplied by the inverse of the co-efficient matrix.This approach is based on the transformation of linear systems described in the SPIKE algorithm and is particularly well-suited for large-scale sparse block tridiagonal matrix structures.It enables efficient,parallel,and flexible solutions while maintaining a certain degree of block diagonal dominance.Compared to directly solving block tridiagonal co-efficient matrices,this method demonstrates appreciable advantages in terms of numerical stability and computational efficiency.Consequently,the new smoothing algorithm yields a new smoother that features fewer constraints and broader applicability than traditional methods.The estimates,such as smoothed state,covariance,and cross-covariance,are essential for fields,such as system identification,navigation,guidance,and control.Finally,the effectiveness of the proposed smoothing algorithm and smoother is validated through numerical simulations.
文摘High-intensity interval training(HIIT),a highly efficient and distinctive exercise format,has sparked growing academic interest in sports performance training.This article synthesizes theoretical and applied evidence to analyze mechanisms of HIIT in neuromuscular activation,hormonal responses,muscle fiber adaptation,and metabolic pathway effects.It focuses on its effectiveness in enhancing explosive power,maximum strength,and strength endurance,while also examining the integration of HIIT with traditional resistance training,periodized programming,and personalized prescription.Scientific implementation of HIIT can effectively diversify or even replace conventional strength training,not only offering positive directional changes for strength development but also introducing innovative approaches to sports performance training practices.
