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Cardiometabolic response to high intensity functional training versus rowing-based high intensity interval training 认领 引用
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作者 Todd A.Astorino Madison Mower +1 位作者 Armando Flores Marissa Flannery 《Sports Medicine and Health Science》 CAS CSCD 2026年第3期311-318,共8页
This study compared the cardiometabolic response between rowing high intensity interval training(HIIT)and high intensity functional training(HIFT).Twenty two adults(age and.max=[25±7]yr and[40±9]mL/kg/min)un... This study compared the cardiometabolic response between rowing high intensity interval training(HIIT)and high intensity functional training(HIFT).Twenty two adults(age and.max=[25±7]yr and[40±9]mL/kg/min)underwent incremental exercise on a rowing ergometer to assess.max and peak power output(PPO).Subsequently,they underwent rowing HIIT(six 1 minutes[min]efforts at 85%PPO with 75 seconds[s]recovery)or HIFT(six 1 min efforts including pushups,jump squats,mountain climbers,and air squats with 75 s recovery).Gas exchange data,heart rate(HR),and blood lactate concentration(BLa)were acquired during exercise and postexercise.These regimens elicited 92%-96%HRmax,with higher peak HR([174±14]b/min vs.[167±15]b/min,p=0.002)and time spent≥85%HRmax([6.1±2.2]min vs.[5.0±2.8]min,p=0.03)for HIFT versus rowing HIIT.Results showed similar peak.between HIFT and HIIT([81±9]vs.[82±8].max,p=0.72),yet lower mean.([1.73±0.38]L/min vs.[1.93±0.50]L/min,p<0.001).Mean and peak ventilation(.)was significantly higher(p<0.05)with HIFT([62±13]L/min and[84±18]L/min vs.[53±15]L/min and[73±19]L/min).BLa was significantly higher with HIFT versus rowing HIIT(p<0.001)and was elevated 15 min post-exercise([7.0±3.0]mM vs.[3.5±1.1]mM).In healthy,active adults,HIFT elicits vigorous intensities similar to traditional HIIT. 展开更多
关键词 High intensity interval training Circuit training Blood lactate concentration Oxygen uptake Calorie expenditure
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Evaluation and forecast of the regional marine innovation ecosystem’s competitiveness:A systematic multivariate grey interval model with spatial proximity effects 认领 引用
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作者 LI Xuemei LI Na DING Song 《Journal of Geographical Sciences》 SCIE CSCD 2026年第2期363-398,共36页
Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competiti... Establishing a Regional Marine Innovation Ecosystem(RMIE)is crucial for advancing China’s maritime power strategy.Concurrently,developing a competitive RMIE serves as a strategic lever to enhance the global competitiveness of China’s marine science sector.However,research on the competitiveness of RMIE is limited.To this end,this study constructs an evaluation index system based on ecological niche theory to assess the competitiveness of RMIE in China from 2008 to 2020.The findings indicate generally fluctuating upward trends in RMIE’s competitiveness,with Shandong,Jiangsu,and Guangdong showing relatively strong positions.Notably,there are significant intra-regional imbalances and inter-regional asynchrony in RMIE’s competitiveness across China’s three major marine economic circles.Recognizing that forecasting RMIE competitiveness can inform policy formulation,this paper proposes a systematic multivariate grey interval prediction model that incorporates spatial proximity effects.This model effectively captures the interval and uncertainty characteristics of RMIE’s competitiveness while considering spatial relationships among regions.Results from comparative analysis,robustness tests,and sensitivity analysis demonstrate its superior applicability and forecasting accuracy.Additionally,interval forecasts and scenario analyses suggest that RMIE competitiveness will maintain stable growth,although unbalanced and unsynchronized development is likely to persist.Overall,the approach developed for evaluating and forecasting RMIE competitiveness offers valuable insights for effective policy formulation. 展开更多
关键词 grey model regional marine innovation ecosystem ecological niche theory multivariate grey interval prediction model spatial proximity effects
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Interval analysis for antenna-radome system electromagnetic performance considering manufacturing and environmental uncertainties 认领 引用
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作者 Guangda Ding Peng Li +4 位作者 Kai Wu Wanye Xu Wei Wang Hang Yuan Wenwu Zhang 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2026年第6期273-285,共13页
Manufacturing and environmental uncertainties can significantly affect the electromagnetic(EM)performance of antenna-radome systems,leading to degradation in key indicators such as reduced transmission coefficient,inc... Manufacturing and environmental uncertainties can significantly affect the electromagnetic(EM)performance of antenna-radome systems,leading to degradation in key indicators such as reduced transmission coefficient,increased boresight error,and shortened radar detection range.To efficiently and accurately quantify these effects,this study proposes a combined strategy that integrates the Physical Optics-based Surface Integral(PO-SI)method with Interval Analysis(IA).The PO-SI method enables accurate modeling of complex radome structures,while IA estimates the upper and lower bounds of EM performance fluctuations by accounting for both manufacturing errors and environmental uncertainties.Compared to Geometric Optics-based methods,the proposed approach(PO-SI-IA)produces more accurate results that closely align with measured data,without reliance on extensive Monte Carlo sampling.Numerical simulations and microwave anechoic chamber experiments validate its accuracy and robustness.This work provides a reliable theoretical basis for uncertainty performance analysis and offers an efficient and flexible tool for EM performance evaluation and design of antennaradome systems in complex operational environments. 展开更多
关键词 Manufacturing error Environmental uncertainties Antenna-radome systems Electromagnetic(EM)performance PO-Based surface integral(PO-SI) Interval analysis
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(Light)Interval-Valued Pre-t-Norms and Their Application in Constructing Interval-Valued QL-Directional Monotonic Fuzzy Implications 认领 引用
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作者 Peng YU Siyu DANG Xiaoliang LI 《Journal of Mathematical Research with Applications》 CSCD 2025年第3期285-303,共19页
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
关键词 (light)interval-valued pre-t-norm aggregation functions interval directional monotonicity interval-valued directional monotonic fuzzy implications
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High-intensity interval training and glycine interventions ameliorate intestinal homeostasis via modulation of gut microbiota and metabolism in aged mice 认领 引用
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作者 Jiahan He Pinshi Ni +7 位作者 Xianfeng Rong Zhi Yu Boming Li Chenkai Zhang Zeyu Zhang Qingqing Wan Wenjing Zhong Fanghui Li 《Food Science and Human Wellness》 SCIE CAS CSCD 2026年第6期2792-2808,共17页
High-intensity interval training(HIIT)and glycine(Gly)have received much attention for demonstrating resistance to age-related eff ects,and the combination of exercise and nutritional strategies is thought to produce ... High-intensity interval training(HIIT)and glycine(Gly)have received much attention for demonstrating resistance to age-related eff ects,and the combination of exercise and nutritional strategies is thought to produce more favorable outcomes for the organism.However,it is unclear whether HIIT and/or Gly supplementation improves intestinal homeostasis in the aged.The study aimed to investigate the eff ects and mechanisms of HIIT and Gly interventions on intestinal homeostasis in aged mice.The results showed that HIIT and Gly interventions increased small intestinal villus length and goblet cell numbers,improved intestinal aging markers,decreased pro-infl ammatory factor expression,and improved age-related intestinal barrier integrity.The HIIT combined with Gly intervention was more benefi cial in slowing down intestinal aging than a single intervention.In addition,HIIT and Gly interventions remodeled the gut microbiota structure,with HIIT intervention increased Alistipes and Akkermansia,Gly intervention increased Lachnospiraceae,Desulfovibrio,and HIIT combined with Gly intervention increasing Dubosiella,Faecalibacterium,Oscillospiraceae_g_uncultured,Blautia,Staphylococcus.Meanwhile,HIIT and Gly interventions to improve body metabolites,including arachidonic acid,indoleacetic acid,methionine,and L-serine,have been associated with the modulation of lipid peroxidation and the expression of ferroptosis resistance.Finally,we observed correlations between gut microbiota,metabolites,inflammation,intestinal barrier integrity,lipid peroxidation,and ferroptosis-related phenotypes in each group.In conclusion,HIIT and Gly improve intestinal homeostasis in aged mice by remodeling gut microbiota and metabolites. 展开更多
关键词 Aging High-intensity interval training Glycine Gut microbiota Metabolism Intestinal homeostasis
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Nonlocal Boundary Value Problems for Nonlinear Fractional Differential Equations with a Disturbance Parameter on the Infinite Interval 认领 引用
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作者 ZHENG Yanping YANG Hui WANG Wenxia 《应用数学》 北大核心 2026年第2期360-372,共13页
This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theo... This paper is concerned with a class of nonlinear fractional differential equations with a disturbance parameter in the integral boundary conditions on the infinite interval.By using Guo-Krasnoselskii fixed point theorem,fixed point index theory and the analytic technique,we give the bifurcation point of the parameter which divides the range of parameter for the existence of at least two,one and no positive solutions for the problem.And,by using a fixed point theorem of generalized concave operator and cone theory,we establish the maximum parameter interval for the existence of the unique positive solution for the problem and show that such a positive solution continuously depends on the parameter.In the end,some examples are given to illustrate our main results. 展开更多
关键词 Boundary value problem Disturbance parameter Infinite interval Bifurcation point Cone
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Employing Interval Grey Relational Analysis in ESG Investment Decision-Making Based on Ratings 认领 引用
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作者 Zhaoyi Zheng 《Proceedings of Business and Economic Studies》 2026年第6期137-143,共7页
ESG ratings have gradually become an important reference basis in investment decisions.Currently,different rating agencies often give significant differences in ESG scores to the same enterprise based on their own ass... ESG ratings have gradually become an important reference basis in investment decisions.Currently,different rating agencies often give significant differences in ESG scores to the same enterprise based on their own assessment criteria,data sources,and weight settings.The inconsistent scores caused by such multi-source heterogeneous data increase the cognitive uncertainty and decision-making complexity of investors when utilizing ESG information,affecting the accuracy and reliability of investment judgments.In this paper,by introducing the Interval Number Grey Relational Analysis(IGRA)method,an enterprise investment ranking model based on multi-source ESG scores is constructed.The scores from different rating agencies are integrated into the form of interval numbers,effectively reflecting the fluctuation range of the scores.And with the help of the grey system theory,the similarity degree between enterprises and ideal reference objects is measured.Realize the comprehensive processing and scientific ranking of multi-dimensional uncertain information.An empirical analysis was conducted based on the ESG rating data to verify the effectiveness of the method.This research provides methods for ESG investment practices and also offers theoretical references for dealing with uncertain investment issues. 展开更多
关键词 Interval number Grey relational analysis ESG rating Uncertainty decision-making
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Age-and gender-specific dynamics and next-generation reference intervals for pepsinogen in northern China 认领 引用
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作者 Miao-Miao Zhang Dong Zhu +1 位作者 Hai-Bin Zhao Xiu-Ying Zhao 《World Journal of Gastroenterology》 SCIE CAS 2025年第31期63-74,共12页
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
关键词 Pepsinogen Reference intervals Next-generation reference intervals Age dynamics Gastric biomarkers Personalized medicine
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Physiological adaptations and performance enhancement with combined blood flow restricted and interval training:A systematic review with meta-analysis 认领 引用 被引量：5
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作者 Mingyue Yin Shengji Deng +4 位作者 Jianfeng Deng Kai Xu George P.Nassis Olivier Girard Yongming Li 《Journal of Sport and Health Science》 SCIE CSCD 2025年第6期131-148,共18页
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(VO2max)(g=0.63,I2=63%),mean power during the Wingate 30-s test(g=0.70,I2=47%),muscle strength(g=0.88,I2=64%),muscle endurance(g=0.43,I2=0%),time to fatigue(g=1.26,I2=86%),and maximal aerobic speed(g=0.74,I2=0%)compared to IT alone.Subgroup analysis indicated that participant characteristics including training status,IT intensity,and IT modes significantly moderated VO2max(subgroup differences:p<0.05).Specifically,IT+BFR showed significantly superior improvements in VO2maxcompared 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 VO2maxchange,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
关键词 Blood flow restricted training Interval training Meta-analysis
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Data-Driven Combination-Interval Prediction for Landslide Displacement Based on Copula and VMD-WOA-KELM Method 认领 引用 被引量：2
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作者 Longqi Li Yunhuang Yang +1 位作者 Tianzhi Zhou Mengyun Wang 《Journal of Earth Science》 SCIE CAS CSCD 2025年第1期291-306,共16页
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
关键词 landslide displacement interval prediction combination method copula Landslides VMD-WOA-KELM
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Failure probability assessment of step-like landslide using a hybrid interval prediction method under uncertain conditions 认领 引用 被引量：1
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作者 Zhou Zheng Yanlong Li +3 位作者 Ye Zhang Lifeng Wen Ting Wang Xinjian Sun 《Journal of Rock Mechanics and Geotechnical Engineering》 SCIE CSCD 2025年第11期7265-7287,共23页
To address prediction errors and limited information extraction in machine learning(ML)-based interval prediction,a hybrid model was proposed for interval estimation and failure assessment of step-like landslides unde... To address prediction errors and limited information extraction in machine learning(ML)-based interval prediction,a hybrid model was proposed for interval estimation and failure assessment of step-like landslides under uncertainty.The model decomposed displacements into trend and periodic components via Variational Mode Decomposition(VMD)and K-shape clustering.The Residual and Moving Block Bootstrap methods were used to generate pseudo datasets.Polynomial regressionwas adopted for trend forecasting,whereas the Dense Convolutional Network(DenseNet)and Long Short-Term Memory(LSTM)networks were employed for periodic displacement prediction.An Extreme Learning Machine(ELM)was used to estimate the noise variance,enabling the construction of Prediction Intervals(PIs)and quantificationof displacement uncertainty.Failure probabilities(Pf)were derived from PIs using an improved tangential angle criterion and reliability analysis.The model was validated on three step-like landslides in the Three Gorges Reservoir Area,achieving stability assessment accuracies of 99.88%(XD01),99.93%(ZG93),99.89%(ZG118),and 100%for ZG110 and ZG111 across the Baishuihe and Bazimen landslides.For the Shuping landslide,the predictions aligned with fieldobservations before and after the 2014–2015 remediation,with Pfremaining near zero post-2015 except for occasional peaks.The model outperformed conventional ML approaches by yielding narrower PIs.At XD01 with 90%PI nominal confidencelevel(PINC),the coverage width-based criterion(CWC)and PI average width(PIAW)were 3.38 mm.The mean values of the PIs exhibited high accuracy,with a Mean Absolute Error(MAE)of 0.28 mm and Root Mean Square Error(RMSE)of 0.39 mm.These results demonstrate the robustness of the proposed model in improving landslide risk assessment and decision-making under uncertainty. 展开更多
关键词 Step-like landslides Failure probability Prediction intervals Deep learning Epistemic uncertainties
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Efficient uncertainty computation method for solving mechanical dynamic systems with a large-scale of interval parameters 认领 引用 被引量：1
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作者 Jinglai Wu Yupeng Duan Yunqing Zhang 《Acta Mechanica Sinica》 SCIE EI CAS CSCD 2025年第10期213-231,共19页
This paper proposes a non-intrusive computational method for mechanical dynamic systems involving a large-scale of interval uncertain parameters,aiming to reduce the computational costs and improve accuracy in determi... This paper proposes a non-intrusive computational method for mechanical dynamic systems involving a large-scale of interval uncertain parameters,aiming to reduce the computational costs and improve accuracy in determining bounds of system response.The screening method is firstly used to reduce the scale of active uncertain parameters.The sequential high-order polynomials surrogate models are then used to approximate the dynamic system’s response at each time step.To reduce the sampling cost of constructing surrogate model,the interaction effect among uncertain parameters is gradually added to the surrogate model by sequentially incorporating samples from a candidate set,which is composed of vertices and inner grid points.Finally,the points that may produce the bounds of the system response at each time step are searched using the surrogate models.The optimization algorithm is used to locate extreme points,which contribute to determining the inner points producing system response bounds.Additionally,all vertices are also checked using the surrogate models.A vehicle nonlinear dynamic model with 72 uncertain parameters is presented to demonstrate the accuracy and efficiency of the proposed uncertain computational method. 展开更多
关键词 Large-scale interval parameters Dynamic systems Screening method High-order polynomials surrogate model Sampling method
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Multi-Timescale Optimization Scheduling of Distribution Networks Based on the Uncertainty Intervals in Source-Load Forecasting 认领 引用 被引量：1
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作者 Huanan Yu Chunhe Ye +3 位作者 Shiqiang Li He Wang Jing Bian Jinling Li 《Energy Engineering》 EI 2025年第6期2417-2448,共32页
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
关键词 Renewable energy distribution networks source-load uncertainty interval flexible scheduling soft actor-critic algorithm optimization model
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Interval multiscale sample entropy:A novel tool for interval-valued time series complexity analysis 认领 引用
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作者 Ping Tang Bao-Gen Li Yang Wang 《Chinese Physics B》 SCIE EI CAS CSCD 2025年第12期164-172,共9页
To analyze the complexity of interval-valued time series(ITSs),a novel interval multiscale sample entropy(IMSE)methodology is proposed in this paper.To validate the effectiveness and feasibility of IMSE in characteriz... To analyze the complexity of interval-valued time series(ITSs),a novel interval multiscale sample entropy(IMSE)methodology is proposed in this paper.To validate the effectiveness and feasibility of IMSE in characterizing ITS complexity,the method is initially implemented on simulated time series.The experimental results demonstrate that IMSE not only successfully identifies series complexity and long-range autocorrelation patterns but also effectively captures the intrinsic relationships between interval boundaries.Furthermore,the test results show that IMSE can also be applied to measure the complexity of multivariate time series of equal length.Subsequently,IMSE is applied to investigate interval temperature series(2000–2023)from four Chinese cities:Shanghai,Kunming,Chongqing,and Nagqu.The results show that IMSE not only distinctly differentiates temperature patterns across cities but also effectively quantifies complexity and long-term autocorrelation in ITSs.All the results indicate that IMSE is an alternative and effective method for studying the complexity of ITSs. 展开更多
关键词 interval multiscale sample entropy interval-valued time series
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Climate warming shortens the time interval between stem-girth and wood biomass production in twelve temperate tree species 认领 引用
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作者 Nipeng Qian Linxu Wang +4 位作者 Gangdun Li Chunchao Dong Zhenzhao Xu Qijing Liu Guang Zhou 《Plant Diversity》 SCIE CAS CSCD 2025年第6期969-980,共12页
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
关键词 Xylem phenology Wood formation Time interval Photoperiod Forcing Precipitation
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Perceptions and recommendations of multiparas and health-related professionals on appropriate birth intervals:A descriptive qualitative study 认领 引用
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作者 Hongyan Liu Xinli Zhu +5 位作者 Zhijing Xu Shuang Liang Ya Liu Xiaojiao Wang Xu Qian Chunyi Gu 《International Journal of Nursing Sciences》 CSCD 2025年第5期469-476,I0003,共8页
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
关键词 Birth interval Health personnel Multipara Perception Risk factor
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Affective valence predictors from real-world based short sprint interval training 认领 引用
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作者 Stefano Benitez-Flores Flavio A.de S.Castro +2 位作者 Eduardo Caldas Costa Daniel Boullosa Todd A.Astorino 《Sports Medicine and Health Science》 CSCD 2025年第3期190-201,共12页
Affective valence is typically positive at exercise intensities below the lactate threshold,yet more aversive responses occur at supra-threshold intensities.Nevertheless,the physiological and psychological predictors ... Affective valence is typically positive at exercise intensities below the lactate threshold,yet more aversive responses occur at supra-threshold intensities.Nevertheless,the physiological and psychological predictors of affective valence during supramaximal intensities including short sprint interval training(sSIT)have not yet been elucidated.Seventeen(7 women/10 men)moderately active young adults(age=[28.2±5.6]years;VO2max[maximum oxygen consumption]=[52.9±8.1]mL·kg-1·min-1;BMI[body mass index]=[242]kg·m-2)completed four low-volume running sSIT sessions(10-4s efforts with 30 s of passive recovery).We recorded participants’heart rate(HR),root mean square of successive differences of normal RR intervals(RMSSD),heart rate recovery(HRR),ratings of perceived exertion(RPE),feeling scale(FS),intention and self-efficacy during,and after each session.Overall,no significant correlation(p>0.05)was found between FS and baseline clinical outcomes.No significant correlation(p>0.05)was detected between FS and any training parameter.No significant correlations were noted between FS and exercise task self-efficacy and intentions(p>0.05).The regression model was significant(F3,61=5.57;p=0.002)and only three variables significantly entered the generated model:ΔHRR_(end-120s end)(p=0.002;VIF=2.58;40.8%),time≥90%HRpeak(p=0.001;VIF=1.26;31.6%),and RMSSDend(p=0.025;VIF=2.23;27.6%).These findings suggest that HR-based measures,particularly those related to in-task stress(time≥90%HRpeak)and acute recovery(ΔHRR_(end-120s end),and RMSSDend),may predict affective valence during real-world sSIT. 展开更多
关键词 Repeated sprint training High-intensity interval training Perceived exertion Physiological response Psychological response Heart rate
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Multi-Interval-Aggregation Failure Point Approximation for Remaining Useful Life Prediction 认领 引用
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作者 Linchuan Fan Xiaolong Chen +1 位作者 Shuo Li Yi Chai 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第3期639-641,共3页
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
关键词 remaining useful life prediction failure point degradation value health indicator multi interval aggregation failure point approximation machine learning based mining degradation information
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A systematic data-driven modelling framework for nonlinear distillation processes incorporating data intervals clustering and new integrated learning algorithm 认领 引用
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作者 Zhe Wang Renchu He Jian Long 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2025年第5期182-199,共18页
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
关键词 Integrated learning algorithm Data intervals clustering Feature selection Application of artificial intelligence in distillation industry Data-driven modelling
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Predictive Motion Envelopes for Offshore Logistics viaα-Cut Intervals 认领 引用
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作者 Suleiman Ibrahim Shelash Mohammad Nijalingappa Yogeesh +3 位作者 Natarajan Raja Ziaulla P.William Asokan Vasudevan 《Sustainable Marine Structures》 2025年第4期36-55,共20页
Offshore logistics operations must continuously balance safety,fuel efficiency,and emissions reduction while navigating under uncertain and highly variable sea states.To address this challenge,we present anα-cut inte... Offshore logistics operations must continuously balance safety,fuel efficiency,and emissions reduction while navigating under uncertain and highly variable sea states.To address this challenge,we present anα-cut interval framework in which environmental uncertainties,specifically wave height and wind speed,are modeled as fuzzy numbers.Their correspondingα-level intervals are systematically propagated through a discrete vessel dynamics model,focusing on surge and heave responses.This procedure generates families of nested motion envelopes that tighten monotonically with increasingα,thereby producing deterministic yet progressively refined safety bounds without relying on full probabilistic distributions.A case study off the Karnataka coast is used to demonstrate the approach for a 20 km offshore supply voyage.Route planning constrained byα-envelopes ensures adherence to vessel structural and stability limits while enabling optimized transit speed.Comparative evaluation indicates that,relative to standard interval analysis,α-cut propagation substantially reduces over-conservatism,while against Monte Carlo-based envelopes it achieves similar coverage with significantly lower computational effort.Sensitivity analyses further quantify the influence ofα-grid resolution,membership-function design,and hydrodynamic coupling coefficients on envelope width,fuel use,and emissions.In the tested scenario,higherαlevels allow up to~15%reduction in worst-case energy consumption and nearly 10%reduction in CO2emissions,all while preserving safety margins.Overall,the proposed framework is transparent,computationally efficient,and easily integrable into digital-twin-enabled operational workflows,providing a practical and sustainable decision-support tool for adaptive offshore logistics planning. 展开更多
关键词 Fuzzy Uncertainty Interval Propagation α‑cut Methodology Vessel Dynamics Route Planning Emis‑sion Analysis
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