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
[Objectives]To synthesize evidence on HIIT versus moderate-intensity continuous training(MICT)or routine rehabilitation in stroke survivors.[Methods]We systematically searched 8 databases(PubMed,EMBASE,CENTRAL,Web of ...[Objectives]To synthesize evidence on HIIT versus moderate-intensity continuous training(MICT)or routine rehabilitation in stroke survivors.[Methods]We systematically searched 8 databases(PubMed,EMBASE,CENTRAL,Web of Science,SPORTSDiscus,PsycINFO,SCOPUS,CINAHL)up to May 2025.Seventeen randomized controlled trials(RCTs;total n=1142)met inclusion criteria:adults with stroke,device-based HIIT(≥70%HRR/VO 2peak),and outcomes assessing VO 2peak,6-min walk distance(6MWD),or Berg Balance Scale(BBS).Methodological quality was evaluated using the PEDro scale.Pooled effect sizes(Hedges'g)were calculated via random-effects models,with heterogeneity quantified by I^(2).[Results]HIIT significantly improved peak oxygen uptake(VO 2peak)versus controls(g=0.59,95%CI:0.44-0.75,p<0.001;I^(2)=16.29%).Low heterogeneity and symmetrical funnel plots supported robustness.HIIT also enhanced walking endurance(6MWD:g=0.32,95%CI:0.16-0.48,p<0.01;I^(2)=30%).In contrast,no significant benefit was observed for balance function(BBS:g=0.07,95%CI:-0.13-0.26,p=0.50;I^(2)=0%).[Conclusions]HIIT is a safe and highly effective intervention for enhancing aerobic capacity and walking function post-stroke.Its benefits are maximized at higher intensities and longer durations but do not extend to balance improvement.Integrating HIIT into stroke rehabilitation protocols is strongly recommended to promote functional independence.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
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
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
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
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
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
Most reliability studies assume large samples or independence among components,but these assump-tions often fail in practice,leading to imprecise inference.We address this issue by constructing confidence intervals(CI...Most reliability studies assume large samples or independence among components,but these assump-tions often fail in practice,leading to imprecise inference.We address this issue by constructing confidence intervals(CIs)for the reliability of two-component systems with Weibull distributed failure times under a copula-frailty framework.Our construction integrates gamma-distributed frailties to capture unobserved heterogeneity and a copula-based dependence structure for correlated failures.The main contribution of this work is to derive adjusted CIs that explicitly incorporate the copula parameter in the variance-covariance matrix,achieving near-nominal coverage probabilities even in small samples or highly dependent settings.Through simulation studies,we show that,although traditional methods may suffice with moderate dependence and large samples,the proposed CIs offer notable benefits when dependence is strong or data are sparse.We further illustrate our construction with a synthetic example illustrating how penalized estimation can mitigate the issue of a degenerate Hessian matrix under high dependence and limited observations,so enabling uncertainty quantification despite deviations from nominal assumptions.Overall,our results fill a gap in reliability modeling for systems prone to correlated failures,and contribute to more robust inference in engineering,industrial,and biomedical applications.展开更多
Background Vibrotactile feedback systems are widely used in assistive technology,wearable devices,and virtual environments to deliver precise tactile information.The timing of interstimulus intervals(ISIs)plays a crit...Background Vibrotactile feedback systems are widely used in assistive technology,wearable devices,and virtual environments to deliver precise tactile information.The timing of interstimulus intervals(ISIs)plays a critical role in determining how accurately users perceive and interpret vibrotactile patterns.The optimal use of ISIs can increase the effectiveness of these systems,improve user interaction,and enable reliable,intuitive feedback in diverse applications.We examined how different interstimulus intervals ISIs impact the accuracy of vibrotactile pattern recognition.Methods Participants wore a forearm-mounted device with six voice coil actuators arranged in a 3×2 grid,delivering Braille-based vibrotactile patterns sequentially at ISIs ranging from 10 to 2500 ms.Eight participants performed identification tasks involving Icelandic Braille patterns categorized as either short(2-3 actuators)or long(4-5 actuators).A repeated measures ANOVA was conducted to assess the effects of ISI,pattern type,and practice(across two testing blocks)on pattern recognition accuracy.Results For short patterns,accuracy was highest(92%-98%)at ISIs of 50-700 ms,with peak performance at 300 ms.For long patterns,accuracy reached 86%-94%at ISIs of 100-500 ms,peaking at 400 ms.Participants were more accurate with short patterns,and performance improved significantly over time for both short and long patterns,highlighting the importance of training for vibrotactile pattern recognition.Conclusions These results underscore the importance of careful selection of ISIs in vibrotactile feedback systems for accurate pattern identification.The findings provide valuable insights for conveying tactile information using wearable devices,contributing to better tactile feedback and performance in applications requiring precise vibrotactile information delivery.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
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
Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway s...Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway subgrade settlement interval prediction method using the secretary bird optimization(SBOA)algorithm to optimize the BP neural network under the premise of gray relational analysis is proposed.Findings–Using the SBOA algorithm to optimize the BP neural network,the optimal weights and thresholds are obtained,and the best parameter prediction model is combined.The data were collected from the sensors deployed through the subgrade settlement monitoring system,and the gray relational analysis is used to verify that all four influencing factors had a great correlation to the subgrade settlement,and the collected data are verified using the model.Originality/value–The experimental results show that the SBOA-BP model has higher prediction accuracy than the BP model,and the SBOA-BP model has a wider range of prediction intervals for a given confidence level,which can provide higher guiding value for practical engineering applications.展开更多
Dear Editor,This letter focuses on the remaining useful life(RUL)prediction task under limited labeled samples.Existing machine-learning-based RUL prediction methods for this task usually pay attention to mining degra...Dear Editor,This letter focuses on the remaining useful life(RUL)prediction task under limited labeled samples.Existing machine-learning-based RUL prediction methods for this task usually pay attention to mining degradation information to improve the prediction accuracy of degradation value or health indicator for the next epoch.However,they ignore the cumulative prediction error caused by iterations before reaching the failure point.展开更多
An Interval Type-2(IT-2)fuzzy controller design approach is proposed in this research to simultaneously achievemultiple control objectives inNonlinearMulti-Agent Systems(NMASs),including formation,containment,and coll...An Interval Type-2(IT-2)fuzzy controller design approach is proposed in this research to simultaneously achievemultiple control objectives inNonlinearMulti-Agent Systems(NMASs),including formation,containment,and collision avoidance.However,inherent nonlinearities and uncertainties present in practical control systems contribute to the challenge of achieving precise control performance.Based on the IT-2 Takagi-Sugeno Fuzzy Model(T-SFM),the fuzzy control approach can offer a more effective solution for NMASs facing uncertainties.Unlike existing control methods for NMASs,the Formation and Containment(F-and-C)control problem with collision avoidance capability under uncertainties based on the IT-2 T-SFM is discussed for the first time.Moreover,an IT-2 fuzzy tracking control approach is proposed to solve the formation task for leaders in NMASs without requiring communication.This control scheme makes the design process of the IT-2 fuzzy Formation Controller(FC)more straightforward and effective.According to the communication interaction protocol,the IT-2 Containment Controller(CC)design approach is proposed for followers to ensure convergence into the region defined by the leaders.Leveraging the IT-2 T-SFM representation,the analysis methods developed for linear Multi-Agent Systems(MASs)are successfully extended to perform containment analysis without requiring the additional assumptions imposed in existing research.Notably,the IT-2 fuzzy tracking controller can also be applied in collision avoidance situations to track the desired trajectories calculated by the avoidance algorithm under the Artificial Potential Field(APF).Benefiting from the combination of vortex and source APFs,the leaders can properly adjust the system dynamics to prevent potential collision risk.Integrating the fuzzy theory and APFs avoidance algorithm,an IT-2 fuzzy controller design approach is proposed to achieve the F-and-C purposewhile ensuring collision avoidance capability.Finally,amulti-ship simulation is conducted to validate the feasibility and effectiveness of the designed IT-2 fuzzy controller.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
For short-term PV power prediction,based on interval type-2 Takagi-Sugeno-Kang fuzzy logic systems(IT2 TSK FLS),combined with improved grey wolf optimizer(IGWO)algorithm,an IGWO-IT2 TSK FLS method was proposed.Compare...For short-term PV power prediction,based on interval type-2 Takagi-Sugeno-Kang fuzzy logic systems(IT2 TSK FLS),combined with improved grey wolf optimizer(IGWO)algorithm,an IGWO-IT2 TSK FLS method was proposed.Compared with the type-1 TSK fuzzy logic system method,interval type-2 fuzzy sets could simultaneously model both intra-personal uncertainty and inter-personal uncertainty based on the training of the existing error back propagation(BP)algorithm,and the IGWO algorithm was used for training the model premise and consequent parameters to further improve the predictive performance of the model.By improving the gray wolf optimization algorithm,the early convergence judgment mechanism,nonlinear cosine adjustment strategy,and Levy flight strategy were introduced to improve the convergence speed of the algorithm and avoid the problem of falling into local optimum.The interval type-2 TSK FLS method based on the IGWO algorithm was applied to the real-world photovoltaic power time series forecasting instance.Under the same conditions,it was also compared with different IT2 TSK FLS methods,such as type I TSK FLS method,BP algorithm,genetic algorithm,differential evolution,particle swarm optimization,biogeography optimization,gray wolf optimization,etc.Experimental results showed that the proposed method based on IGWO algorithm outperformed other methods in performance,showing its effectiveness and application potential.展开更多
Purpose We aimed to determine:(a)the chronic effects of interval training(IT)combined with blood flow restriction(BFR)on physiological adaptations(aerobic/anaerobic capacity and muscle responses)and performance enhanc...Purpose We aimed to determine:(a)the chronic effects of interval training(IT)combined with blood flow restriction(BFR)on physiological adaptations(aerobic/anaerobic capacity and muscle responses)and performance enhancement(endurance and sprints),and(b)the influence of participant characteristics and intervention protocols on these effects.Methods Searches were conducted in PubMed,Web of Science(Core Collection),Cochrane Library(Embase,ClinicalTrials.gov,and International Clinical Trials Registry Platform),and Chinese National Knowledge Infrastructure on April 2,with updates on October 17,2024.Pooled effects for each outcome were summarized using Hedge's g(g)through meta-analysis-based random effects models,and subgroup and regression analyses were used to explore moderators.Results A total of 24 studies with 621 participants were included.IT combined with BFR(IT+BFR)significantly improved maximal oxygen uptake(VO2_(max))(g=0.63,I^(2)=63%),mean power during the Wingate 30-s test(g=0.70,I^(2)=47%),muscle strength(g=0.88,I^(2)=64%),muscle endurance(g=0.43,I^(2)=0%),time to fatigue(g=1.26,I^(2)=86%),and maximal aerobic speed(g=0.74,I^(2)=0%)compared to IT alone.Subgroup analysis indicated that participant characteristics including training status,IT intensity,and IT modes significantly moderated VO2_(max)(subgroup differences:p<0.05).Specifically,IT+BFR showed significantly superior improvements in VO2_(max)compared to IT alone in trained individuals(g=0.76)at supra-maximal intensity(g=1.29)and moderate intensity(g=1.08)as well as in walking(g=1.64)and running(g=0.63)modes.Meta-regression analysis showed cuff width(β=0.14)was significantly associated with VO2_(max)change,identifying 8.23 cm as the minimum threshold required for significant improvement.Subgroup analyses regarding muscle strength did not reveal any significant moderators.Conclusion IT+BFR enhances physiological adaptations and optimizes aspects of endurance performance,with moderators including training status,IT protocol(intensity,mode,and type),and cuff width.This intervention addresses various IT-related challenges and provides tailored protocols and benefits for diverse populations.展开更多
Interval-valued pre-aggregation functions are a hot topic in the research of aggregation functions and have received considerable attention in recent years.As a special class of interval-valued pre-aggregation functio...Interval-valued pre-aggregation functions are a hot topic in the research of aggregation functions and have received considerable attention in recent years.As a special class of interval-valued pre-aggregation functions,(light)interval-valued pre-t-norms were initially proposed by Wang and Hu,but their properties were not further discussed by the authors.The main purpose of this paper is to study in depth the properties and generation of(light)intervalvalued pre-t-norms.Firstly,several properties of(light)interval-valued pre-t-norms and their relationship with(light)pre-t-norms are presented.Then,two different generation methods for(light)interval-valued pre-t-norms are introduced.Finally,it demonstrates a specific application of(light)interval-valued pre-t-norms in constructing interval-valued directional monotonic fuzzy implications,namely,using the(light)interval-valued pre-t-norm IT,interval-valued fuzzy negations IN,and(light)interval-valued pre-t-conorm IS to construct interval-valued QL-directional monotonic operations.展开更多
The distillation process is an important chemical process,and the application of data-driven modelling approach has the potential to reduce model complexity compared to mechanistic modelling,thus improving the efficie...The distillation process is an important chemical process,and the application of data-driven modelling approach has the potential to reduce model complexity compared to mechanistic modelling,thus improving the efficiency of process optimization or monitoring studies.However,the distillation process is highly nonlinear and has multiple uncertainty perturbation intervals,which brings challenges to accurate data-driven modelling of distillation processes.This paper proposes a systematic data-driven modelling framework to solve these problems.Firstly,data segment variance was introduced into the K-means algorithm to form K-means data interval(KMDI)clustering in order to cluster the data into perturbed and steady state intervals for steady-state data extraction.Secondly,maximal information coefficient(MIC)was employed to calculate the nonlinear correlation between variables for removing redundant features.Finally,extreme gradient boosting(XGBoost)was integrated as the basic learner into adaptive boosting(AdaBoost)with the error threshold(ET)set to improve weights update strategy to construct the new integrated learning algorithm,XGBoost-AdaBoost-ET.The superiority of the proposed framework is verified by applying this data-driven modelling framework to a real industrial process of propylene distillation.展开更多
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[Objectives]To synthesize evidence on HIIT versus moderate-intensity continuous training(MICT)or routine rehabilitation in stroke survivors.[Methods]We systematically searched 8 databases(PubMed,EMBASE,CENTRAL,Web of Science,SPORTSDiscus,PsycINFO,SCOPUS,CINAHL)up to May 2025.Seventeen randomized controlled trials(RCTs;total n=1142)met inclusion criteria:adults with stroke,device-based HIIT(≥70%HRR/VO 2peak),and outcomes assessing VO 2peak,6-min walk distance(6MWD),or Berg Balance Scale(BBS).Methodological quality was evaluated using the PEDro scale.Pooled effect sizes(Hedges'g)were calculated via random-effects models,with heterogeneity quantified by I^(2).[Results]HIIT significantly improved peak oxygen uptake(VO 2peak)versus controls(g=0.59,95%CI:0.44-0.75,p<0.001;I^(2)=16.29%).Low heterogeneity and symmetrical funnel plots supported robustness.HIIT also enhanced walking endurance(6MWD:g=0.32,95%CI:0.16-0.48,p<0.01;I^(2)=30%).In contrast,no significant benefit was observed for balance function(BBS:g=0.07,95%CI:-0.13-0.26,p=0.50;I^(2)=0%).[Conclusions]HIIT is a safe and highly effective intervention for enhancing aerobic capacity and walking function post-stroke.Its benefits are maximized at higher intensities and longer durations but do not extend to balance improvement.Integrating HIIT into stroke rehabilitation protocols is strongly recommended to promote functional independence.
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 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.
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.
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 Colombian government through COLCIENCIA scholarships,National Doctoral Program,Call 727 of 2015C.Castro gratefully acknowledges partial financial support from the Centro de Matematica da Universidade do Minho(CMAT/UM),through UID/00013V.Leiva acknowledges funding from the Agencia Nacional de Investigacion y Desarrollo(ANID)of the Chilean Ministry of Science,Technology,Knowledge and Innovation,through FONDECYT project grant 1200525.
文摘Most reliability studies assume large samples or independence among components,but these assump-tions often fail in practice,leading to imprecise inference.We address this issue by constructing confidence intervals(CIs)for the reliability of two-component systems with Weibull distributed failure times under a copula-frailty framework.Our construction integrates gamma-distributed frailties to capture unobserved heterogeneity and a copula-based dependence structure for correlated failures.The main contribution of this work is to derive adjusted CIs that explicitly incorporate the copula parameter in the variance-covariance matrix,achieving near-nominal coverage probabilities even in small samples or highly dependent settings.Through simulation studies,we show that,although traditional methods may suffice with moderate dependence and large samples,the proposed CIs offer notable benefits when dependence is strong or data are sparse.We further illustrate our construction with a synthetic example illustrating how penalized estimation can mitigate the issue of a degenerate Hessian matrix under high dependence and limited observations,so enabling uncertainty quantification despite deviations from nominal assumptions.Overall,our results fill a gap in reliability modeling for systems prone to correlated failures,and contribute to more robust inference in engineering,industrial,and biomedical applications.
基金Supported by the Icelandic Technological Development Fund(Project No.1910271).
文摘Background Vibrotactile feedback systems are widely used in assistive technology,wearable devices,and virtual environments to deliver precise tactile information.The timing of interstimulus intervals(ISIs)plays a critical role in determining how accurately users perceive and interpret vibrotactile patterns.The optimal use of ISIs can increase the effectiveness of these systems,improve user interaction,and enable reliable,intuitive feedback in diverse applications.We examined how different interstimulus intervals ISIs impact the accuracy of vibrotactile pattern recognition.Methods Participants wore a forearm-mounted device with six voice coil actuators arranged in a 3×2 grid,delivering Braille-based vibrotactile patterns sequentially at ISIs ranging from 10 to 2500 ms.Eight participants performed identification tasks involving Icelandic Braille patterns categorized as either short(2-3 actuators)or long(4-5 actuators).A repeated measures ANOVA was conducted to assess the effects of ISI,pattern type,and practice(across two testing blocks)on pattern recognition accuracy.Results For short patterns,accuracy was highest(92%-98%)at ISIs of 50-700 ms,with peak performance at 300 ms.For long patterns,accuracy reached 86%-94%at ISIs of 100-500 ms,peaking at 400 ms.Participants were more accurate with short patterns,and performance improved significantly over time for both short and long patterns,highlighting the importance of training for vibrotactile pattern recognition.Conclusions These results underscore the importance of careful selection of ISIs in vibrotactile feedback systems for accurate pattern identification.The findings provide valuable insights for conveying tactile information using wearable devices,contributing to better tactile feedback and performance in applications requiring precise vibrotactile information delivery.
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.
文摘Purpose–The deformation of the roadbed is easily influenced by the external environment to improve the accuracy of high-speed railway subgrade settlement prediction.Design/methodology/approach–A high-speed railway subgrade settlement interval prediction method using the secretary bird optimization(SBOA)algorithm to optimize the BP neural network under the premise of gray relational analysis is proposed.Findings–Using the SBOA algorithm to optimize the BP neural network,the optimal weights and thresholds are obtained,and the best parameter prediction model is combined.The data were collected from the sensors deployed through the subgrade settlement monitoring system,and the gray relational analysis is used to verify that all four influencing factors had a great correlation to the subgrade settlement,and the collected data are verified using the model.Originality/value–The experimental results show that the SBOA-BP model has higher prediction accuracy than the BP model,and the SBOA-BP model has a wider range of prediction intervals for a given confidence level,which can provide higher guiding value for practical engineering applications.
基金supported in part by the National Natural Science Foundation of China(U2034209)the Postdoctoral Science Foundation of Chongqing(cstc2021jcyj-bsh X0047)+1 种基金the Fundamental Research Funds for the Central Universities(2022CDJJMRH-008)the National Natural Science Foundation of China(62203075)
文摘Dear Editor,This letter focuses on the remaining useful life(RUL)prediction task under limited labeled samples.Existing machine-learning-based RUL prediction methods for this task usually pay attention to mining degradation information to improve the prediction accuracy of degradation value or health indicator for the next epoch.However,they ignore the cumulative prediction error caused by iterations before reaching the failure point.
基金founded by the National Science and Technology Council of the Republic of China under contract NSTC113-2221-E-019-032.
文摘An Interval Type-2(IT-2)fuzzy controller design approach is proposed in this research to simultaneously achievemultiple control objectives inNonlinearMulti-Agent Systems(NMASs),including formation,containment,and collision avoidance.However,inherent nonlinearities and uncertainties present in practical control systems contribute to the challenge of achieving precise control performance.Based on the IT-2 Takagi-Sugeno Fuzzy Model(T-SFM),the fuzzy control approach can offer a more effective solution for NMASs facing uncertainties.Unlike existing control methods for NMASs,the Formation and Containment(F-and-C)control problem with collision avoidance capability under uncertainties based on the IT-2 T-SFM is discussed for the first time.Moreover,an IT-2 fuzzy tracking control approach is proposed to solve the formation task for leaders in NMASs without requiring communication.This control scheme makes the design process of the IT-2 fuzzy Formation Controller(FC)more straightforward and effective.According to the communication interaction protocol,the IT-2 Containment Controller(CC)design approach is proposed for followers to ensure convergence into the region defined by the leaders.Leveraging the IT-2 T-SFM representation,the analysis methods developed for linear Multi-Agent Systems(MASs)are successfully extended to perform containment analysis without requiring the additional assumptions imposed in existing research.Notably,the IT-2 fuzzy tracking controller can also be applied in collision avoidance situations to track the desired trajectories calculated by the avoidance algorithm under the Artificial Potential Field(APF).Benefiting from the combination of vortex and source APFs,the leaders can properly adjust the system dynamics to prevent potential collision risk.Integrating the fuzzy theory and APFs avoidance algorithm,an IT-2 fuzzy controller design approach is proposed to achieve the F-and-C purposewhile ensuring collision avoidance capability.Finally,amulti-ship simulation is conducted to validate the feasibility and effectiveness of the designed IT-2 fuzzy controller.
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 National Natural Science Foundation of China(No.12172157)Key Project of Natural Science Foundation of Gansu Province(No.25JRRA150)Key Research and Development Planning Project of Gansu Province(No.23YFWA0007).
文摘For short-term PV power prediction,based on interval type-2 Takagi-Sugeno-Kang fuzzy logic systems(IT2 TSK FLS),combined with improved grey wolf optimizer(IGWO)algorithm,an IGWO-IT2 TSK FLS method was proposed.Compared with the type-1 TSK fuzzy logic system method,interval type-2 fuzzy sets could simultaneously model both intra-personal uncertainty and inter-personal uncertainty based on the training of the existing error back propagation(BP)algorithm,and the IGWO algorithm was used for training the model premise and consequent parameters to further improve the predictive performance of the model.By improving the gray wolf optimization algorithm,the early convergence judgment mechanism,nonlinear cosine adjustment strategy,and Levy flight strategy were introduced to improve the convergence speed of the algorithm and avoid the problem of falling into local optimum.The interval type-2 TSK FLS method based on the IGWO algorithm was applied to the real-world photovoltaic power time series forecasting instance.Under the same conditions,it was also compared with different IT2 TSK FLS methods,such as type I TSK FLS method,BP algorithm,genetic algorithm,differential evolution,particle swarm optimization,biogeography optimization,gray wolf optimization,etc.Experimental results showed that the proposed method based on IGWO algorithm outperformed other methods in performance,showing its effectiveness and application potential.
文摘Purpose We aimed to determine:(a)the chronic effects of interval training(IT)combined with blood flow restriction(BFR)on physiological adaptations(aerobic/anaerobic capacity and muscle responses)and performance enhancement(endurance and sprints),and(b)the influence of participant characteristics and intervention protocols on these effects.Methods Searches were conducted in PubMed,Web of Science(Core Collection),Cochrane Library(Embase,ClinicalTrials.gov,and International Clinical Trials Registry Platform),and Chinese National Knowledge Infrastructure on April 2,with updates on October 17,2024.Pooled effects for each outcome were summarized using Hedge's g(g)through meta-analysis-based random effects models,and subgroup and regression analyses were used to explore moderators.Results A total of 24 studies with 621 participants were included.IT combined with BFR(IT+BFR)significantly improved maximal oxygen uptake(VO2_(max))(g=0.63,I^(2)=63%),mean power during the Wingate 30-s test(g=0.70,I^(2)=47%),muscle strength(g=0.88,I^(2)=64%),muscle endurance(g=0.43,I^(2)=0%),time to fatigue(g=1.26,I^(2)=86%),and maximal aerobic speed(g=0.74,I^(2)=0%)compared to IT alone.Subgroup analysis indicated that participant characteristics including training status,IT intensity,and IT modes significantly moderated VO2_(max)(subgroup differences:p<0.05).Specifically,IT+BFR showed significantly superior improvements in VO2_(max)compared to IT alone in trained individuals(g=0.76)at supra-maximal intensity(g=1.29)and moderate intensity(g=1.08)as well as in walking(g=1.64)and running(g=0.63)modes.Meta-regression analysis showed cuff width(β=0.14)was significantly associated with VO2_(max)change,identifying 8.23 cm as the minimum threshold required for significant improvement.Subgroup analyses regarding muscle strength did not reveal any significant moderators.Conclusion IT+BFR enhances physiological adaptations and optimizes aspects of endurance performance,with moderators including training status,IT protocol(intensity,mode,and type),and cuff width.This intervention addresses various IT-related challenges and provides tailored protocols and benefits for diverse populations.
基金the National Natural Science Foundation of China(Grant No.12171294)。
文摘Interval-valued pre-aggregation functions are a hot topic in the research of aggregation functions and have received considerable attention in recent years.As a special class of interval-valued pre-aggregation functions,(light)interval-valued pre-t-norms were initially proposed by Wang and Hu,but their properties were not further discussed by the authors.The main purpose of this paper is to study in depth the properties and generation of(light)intervalvalued pre-t-norms.Firstly,several properties of(light)interval-valued pre-t-norms and their relationship with(light)pre-t-norms are presented.Then,two different generation methods for(light)interval-valued pre-t-norms are introduced.Finally,it demonstrates a specific application of(light)interval-valued pre-t-norms in constructing interval-valued directional monotonic fuzzy implications,namely,using the(light)interval-valued pre-t-norm IT,interval-valued fuzzy negations IN,and(light)interval-valued pre-t-conorm IS to construct interval-valued QL-directional monotonic operations.
基金supported by the National Key Research and Development Program of China(2023YFB3307801)the National Natural Science Foundation of China(62394343,62373155,62073142)+3 种基金Major Science and Technology Project of Xinjiang(No.2022A01006-4)the Programme of Introducing Talents of Discipline to Universities(the 111 Project)under Grant B17017the Fundamental Research Funds for the Central Universities,Science Foundation of China University of Petroleum,Beijing(No.2462024YJRC011)the Open Research Project of the State Key Laboratory of Industrial Control Technology,China(Grant No.ICT2024B70).
文摘The distillation process is an important chemical process,and the application of data-driven modelling approach has the potential to reduce model complexity compared to mechanistic modelling,thus improving the efficiency of process optimization or monitoring studies.However,the distillation process is highly nonlinear and has multiple uncertainty perturbation intervals,which brings challenges to accurate data-driven modelling of distillation processes.This paper proposes a systematic data-driven modelling framework to solve these problems.Firstly,data segment variance was introduced into the K-means algorithm to form K-means data interval(KMDI)clustering in order to cluster the data into perturbed and steady state intervals for steady-state data extraction.Secondly,maximal information coefficient(MIC)was employed to calculate the nonlinear correlation between variables for removing redundant features.Finally,extreme gradient boosting(XGBoost)was integrated as the basic learner into adaptive boosting(AdaBoost)with the error threshold(ET)set to improve weights update strategy to construct the new integrated learning algorithm,XGBoost-AdaBoost-ET.The superiority of the proposed framework is verified by applying this data-driven modelling framework to a real industrial process of propylene distillation.
