Objective:The causal relationship between eczema and autoimmune diseases has not been previously reported.This study aims to evaluate the causal relationship between eczema and autoimmune diseases.Methods:The two‐sam...Objective:The causal relationship between eczema and autoimmune diseases has not been previously reported.This study aims to evaluate the causal relationship between eczema and autoimmune diseases.Methods:The two‐sample Mendelian randomization(MR)method was used to assess the causal effect of eczema on autoimmune diseases.Summary data from the Genome-Wide Association Study Catalog(GWAS)were obtained from the Integrative Epidemiology Unit(IEU)database.For eczema and autoimmune diseases,genetic instrument variants(GIVs)were identified according to the significant difference(P<5×10−8).Causal effect estimates were generated using the inverse‐variance weighted(IVW)method.MR Egger,maximum likelihood,MR-PRESSO,and MR-RAPS methods were used for alternative analyses.Sensitivity tests,including heterogeneity,horizontal pleiotropy,and leave-one-out analyses,were performed.Finally,reverse causality was assessed.Results:Genetic susceptibility to eczema was associated with an increased risk of Crohn’s disease(OR=1.444,95%CI 1.199 to 1.738,P<0.001)and ulcerative colitis(OR=1.002,95%CI 1.001 to 1.003,P=0.002).However,no causal relationship was found for the other 6 autoimmune diseases,including systemic lupus erythematosus(SLE)(OR=0.932,P=0.401),bullous pemphigoid(BP)(OR=1.191,P=0.642),vitiligo(OR=1.000,P=0.327),multiple sclerosis(MS)(OR=1.000,P=0.965),ankylosing spondylitis(AS)(OR=1.001,P=0.121),rheumatoid arthritis(RA)(OR=1.000,P=0.460).Additionally,no reverse causal relationship was found between autoimmune diseases and eczema.Conclusion:Eczema is associated with an increased risk of Crohn’s disease and ulcerative colitis.No causal relationship is found between eczema and SLE,MS,AS,RA,BP,or vitiligo.展开更多
Mendelian randomization(MR)is widely used in causal mediation analysis to control unmeasured confounding effects,which is valid under some strong assumptions.It is thus of great interest to assess the impact of violat...Mendelian randomization(MR)is widely used in causal mediation analysis to control unmeasured confounding effects,which is valid under some strong assumptions.It is thus of great interest to assess the impact of violations of these MR assumptions through sensitivity analysis.Sensitivity analyses have been conducted for simple MR-based causal average effect analyses,but they are not available for MR-based mediation analysis studies,and we aim to fill this gap in this paper.We propose to use two sensitivity parameters to quantify the effect due to the deviation of the IV assumptions.With these two sensitivity parameters,we derive consistent indirect causal effect estimators and establish their asymptotic propersties.Our theoretical results can be used in MR-based mediation analysis to study the impact of violations of MR as-sumptions.The finite sample performance of the proposed method is illustrated through simulation studies,sensitivity ana-lysis,and application to a real genome-wide association study.展开更多
Objective:Gut microbiota(GM)and blood metabolites are associated with the development of urticaria,yet their specific causal relationships in East Asian populations remain unclear.This study aims to elucidate the caus...Objective:Gut microbiota(GM)and blood metabolites are associated with the development of urticaria,yet their specific causal relationships in East Asian populations remain unclear.This study aims to elucidate the causal and mediating relationships among GM,blood metabolites,and urticaria in East Asians using Mendelian randomization(MR)analysis.Methods:Summary-level statistics for 500 GM taxa,112 blood metabolites,and urticaria were obtained from publicly available Genome-Wide Association Studies(GWAS)datasets.Bidirectional MR analyses were performed to examine causal associations among the GM,blood metabolites,and urticaria.The inverse variance weighted(IVW)method served as the primary analytical approach,supplemented by MR-Egger,weighted median,simple mode,and weighted mode methods.Sensitivity analyses included heterogeneity tests,horizontal pleiotropy assessments,and leave-one-out analyses.Mediation analysis was conducted to evaluate the potential mediating effects of blood metabolites on the causal pathways between GM and urticaria.Results:MR analyses identified 12 GM taxa exhibiting significant causal effects on urticaria susceptibility.Nine taxa,such as MF0017_galactose_degradation(OR=1.461,95%CI 1.098 to 1.944,P=0.009),were associated with increased urticaria risk.Three taxa,such as MF0001_arabinoxylan_degradation(OR=0.846,95%CI 0.737 to 0.973,P=0.019),showed protective effects with increased abundance.Additionally,6 blood metabolites demonstrated causal associations with urticaria.Notably,the risk of developing urticaria increases with rising fasting plasma glucose(FPG)levels(OR=1.971,95%CI 1.089 to 3.567,P=0.025).Mediation analysis further demonstrated that FPG partially mediated the protective effect of MF0001_arabinoxylan_degradation on urticaria,accounting for 11.30%of the total effect.Conclusion:This study has delineated specific GM taxa and blood metabolites that hold causal relevance to urticaria in East Asian populations.Notably,arabinogalactan degradation potentially mitigates urticaria risk via reducing FPG concentrations,offering genetic evidence to support therapeutic strategies targeting GM modulation and glucose regulation.展开更多
Creutzfeldt-Jakob disease(CJD)is a rare neurodegenerative disorder characterized by abnormalities in the prion protein(PrP),the most common form of human prion disease.Although Genome-Wide Association Studies(GWAS)hav...Creutzfeldt-Jakob disease(CJD)is a rare neurodegenerative disorder characterized by abnormalities in the prion protein(PrP),the most common form of human prion disease.Although Genome-Wide Association Studies(GWAS)have identified numerous risk genes for CJD,the mechanisms underlying these risk loci remain poorly understood.This study aims to elucidate novel genetically prioritized candidate proteins associated with CJD in the human brain through an integrative analytical pipeline.Utilizing datasets from Protein Quantitative Trait Loci(pQTL)(NpQTL1=152,NpQTL2=376),expression QTL(eQTL)(N=452),and the CJD GWAS(NCJD=4110,NControls=13569),we implemented a systematic analytical pipeline.This pipeline included Proteome-Wide Association Study(PWAS),Mendelian randomization(MR),Bayesian colocalization,and Transcriptome-Wide Association Study(TWAS)to identify novel genetically prioritized candidate proteins implicated in CJD pathogenesis within the brain.Through PWAS,we identified that the altered abundance of six brain proteins was significantly associated with CJD.Two genes,STX6 and PDIA4,were established as lead causal genes for CJD,supported by robust evidence(False Discovery Rate<0.05 in MR analysis;PP4/(PP3+PP4)≥0.75 in Bayesian colocalization).Specifically,elevated levels of STX6 and PDIA4 were associated with an increased risk of CJD.Additionally,TWAS demonstrated that STX6 and PDIA4 were associated with CJD at the transcriptional level.展开更多
OBJECTIVE To investigate the intervention effects of tissue-bone homeostasis manipulation(TBHM)on peripatellar biomechanical parameters and knee joint function in knee osteoarthritis(KOA)patients.METHODS Sixty patient...OBJECTIVE To investigate the intervention effects of tissue-bone homeostasis manipulation(TBHM)on peripatellar biomechanical parameters and knee joint function in knee osteoarthritis(KOA)patients.METHODS Sixty patients with KOA(Kellgren-Lawrence gradeⅡ-Ⅲ)were recruited from the Acupuncture-Moxibustion Rehabilitation Department,Anhui University of Chinese Medicine between October 2024 and May 2025.Participants were randomized into a TBHM group(n=30)or a transcutaneous electrical neuromuscular stimulation(TENS)group(n=30).Using two-way repeated measures ANOVA,biomechanical indicators,including rectus femoris tension,vastus medialis tension,vastus lateralis tension,patellar ligament tension,lateral patellar displacement(LPD),medial patellar displacement(MPD),normalized patellar mobility(LPD/patellar width[PW],MPD/PW),knee flexion range of motion,and functional indicators,including KOOS subscales,time up and go test(TUGT),were compared between groups at baseline and after 6 weeks of intervention.RESULTS After intervention,all biomechanical and knee joint function indicators in the TBHM group were significantly improved(P<0.05,P<0.01),while only the vastus medialis tension,TUGT and KOOS Pain,ADL and QoL scores in the control group were significantly improved(P<0.01).The improvement amplitudes of biomechanical indicators in the TBHM group,including rectus femoris tension,vastus lateralis tension,patellar ligament tension,MPD/PW,LPD/PW and knee flexion range of motion were better than those in the control group(P<0.05,P<0.01).In the functional evaluation,the interaction effects of the TBHM group in all dimensions of the KOOS score and TUGT were statistically significant(P<0.05,P<0.01).Post-hoc simple effect analysis confirmed that there were significant differences in the above indicators between the two groups after intervention(P<0.05),and all indicators showed a significant main effect of time(P<0.01),suggesting that the intervention measures had continuous and cumulative curative effects.CONCLUSION TBHM effectively improves joint function and quality of life in KOA patients by restoring dynamic equilibrium in soft tissue tension and patellar mobility,ultimately achieving the therapeutic goal of concurrent tissue-bone management.展开更多
In this paper,large deviations principle(LDP)and moderate deviations principle(MDP)of record numbers in random walks are studied under certain conditions.The results show that the rate functions of LDP and MDP are dif...In this paper,large deviations principle(LDP)and moderate deviations principle(MDP)of record numbers in random walks are studied under certain conditions.The results show that the rate functions of LDP and MDP are different from those of weak record numbers,which are interesting complements of the conclusions by Li and Yao[1].展开更多
The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the...The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.展开更多
In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergen...In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.展开更多
Missiles provide long-range precision strike capabilities and have become a cornerstone of modern warfare.The contrail clouds formed by missile during their active flight phase present significant chal-lenges to high-...Missiles provide long-range precision strike capabilities and have become a cornerstone of modern warfare.The contrail clouds formed by missile during their active flight phase present significant chal-lenges to high-altitude environmental observation and target detection and tracking.Existing studies primarily focus on specific airspace regions,leaving critical gaps in understanding the effects of long dispersion times,wide altitude ranges,and variable atmospheric conditions on missile contrail clouds.To address these gaps,this article develops a numerical method based on the Lagrangian random walk model,which incorporates various velocity variation terms,including particle velocity caused by the difference of wind field,by the thermal motion of local gas molecules and by random collisions between contrail cloud particles to capture the influence of environmental wind fields,atmospheric conditions,and particle concentrations on the motion of contrail cloud particles.A general coordinate system aligned with the missile's flight trajectory is employed to represent particle distribution characteristics.The proposed method is in good agreement with the conducted experiments as well as with the available numerical simulations.The results demonstrate that the proposed model effectively simulates the dispersion state of contrail clouds,accurately reflecting the impact of large-scale wind field variations and altitude changes with high computational efficiency.Additionally,simulation results indicate that the increased distance between gas molecules in rarefied environments facilitates enhanced particle dispersion,while larger particles exhibit a faster dispersion rate due to their greater mass.展开更多
This paper proposes a longitudinal vulnerability-based analysis method to evaluate the impact of foundation pit excavation on shield tunnels,accounting for geological uncertainties.First,the shield tunnel is modeled a...This paper proposes a longitudinal vulnerability-based analysis method to evaluate the impact of foundation pit excavation on shield tunnels,accounting for geological uncertainties.First,the shield tunnel is modeled as an Euler Bernoulli beam resting on the Pasternak foundation incorporating variability in subgrade parameters along the tunnel’s length.A random analysis method using random field theory is introduced to evaluate the tunnel’s longitudinal responses to excavation.Next,a risk assessment index system is established.The normalized relative depth between the excavation and the shield tunnel is used as a risk index,while the maximum longitudinal deformation,the maximum circumferential opening,and the maximum longitudinal bending moment serve as performance indicators.Based on these,a method for analyzing the longitudinal fragility of shield tunnels under excavation-induced disturbances is proposed.Finally,the technique is applied to a case study involving a foundation pit excavation above a shield tunnel,which is the primary application scenario of this method.Vulnerability curves for different performance indicators are derived,and the effects of tunnel stiffness and subgrade stiffness on the tunnel vulnerability are explored.The results reveal significant differences in vulnerability curves depending on the performance index used.Compared to the maximum circumferential opening and the maximum longitudinal bending moment,selecting the maximum longitudinal deformation as the control index better ensures the tunnel’s usability and safety under excavation disturbances.The longitudinal vulnerability of the shield tunnel nonlinearly decreases with the increase of the tunnel stiffness and subgrade stiffness,and the subgrade stiffness has a more pronounced effect.Parametric analyses suggest that actively reinforcing the substratum is more effective on reducing the risk of tunnel failure due to adjacent excavations than passive reinforcement of the tunnel structure.展开更多
A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,wh...A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,which reduces the risk of penetrating the bulkhead.In the realm of hypervelocity impact,strain rate(>10^(5)s^(-1))effects are negligible,and fluid dynamics is employed to describe the impact process.Efficient numerical tools for precisely predicting the damage degree can greatly accelerate the design and optimization of advanced protective structures.Current hypervelocity impact research primarily focuses on the interaction between projectile and front plate and the movement of debris cloud.However,the damage mechanism of debris cloud impacts on rear plates-the critical threat component-remains underexplored owing to complex multi-physics processes and prohibitive computational costs.Existing approaches,ranging from semi-empirical equations to a machine learningbased ballistic limit prediction method,are constrained to binary penetration classification.Alternatively,the uneven data from experiments and simulations caused these methods to be ineffective when the projectile has irregular shapes and complicate flight attitude.Therefore,it is urgent to develop a new damage prediction method for predicting the rear plate damage,which can help to gain a deeper understanding of the damage mechanism.In this study,a machine learning(ML)method is developed to predict the damage distribution in the rear plate.Based on the unit velocity space,the discretized information of debris cloud and rear plate damage from rare simulation cases is used as input data for training the ML models,while the generalization ability for damage distribution prediction is tested by other simulation cases with different attack angles.The results demonstrate that the training and prediction accuracies using the Random Forest(RF)algorithm significantly surpass those using Artificial Neural Networks(ANNs)and Support Vector Machine(SVM).The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect.This study establishes an expandable new dataset that accommodates additional parameters to improve the prediction accuracy.Results demonstrate the model's ability to overcome data imbalance limitations through debris cloud features,enabling rapid and accurate rear plate damage prediction across wider scenarios with minimal data requirements.展开更多
Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a vi...Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.展开更多
开放领域新词发现研究对于中文自然语言处理的性能提升有着重要的意义.利用条件随机场(condition random field,简称CRF)可对序列输入标注的特点,将新词发现问题转化为预测已分词词语边界是否为新词边界的问题.在对海量规模中文互联网...开放领域新词发现研究对于中文自然语言处理的性能提升有着重要的意义.利用条件随机场(condition random field,简称CRF)可对序列输入标注的特点,将新词发现问题转化为预测已分词词语边界是否为新词边界的问题.在对海量规模中文互联网语料进行分析挖掘的基础上,提出了一系列区分新词边界的统计特征,并采用CRF方法综合这些特征实现了开放领域新词发现的算法,同时比较了K-Means聚类、等频率、基于信息增益这3种离散化方法对新词发现结果的影响.通过在SogouT大规模中文语料库上的新词发现实验,验证了所提出的方法有较好的效果.展开更多
基金This work was supported by the National Natural Science Foundation (82273506,82273508)the Hunan Provincial Health Commission Scientific Research Plan Project (D202304128334),China。
文摘Objective:The causal relationship between eczema and autoimmune diseases has not been previously reported.This study aims to evaluate the causal relationship between eczema and autoimmune diseases.Methods:The two‐sample Mendelian randomization(MR)method was used to assess the causal effect of eczema on autoimmune diseases.Summary data from the Genome-Wide Association Study Catalog(GWAS)were obtained from the Integrative Epidemiology Unit(IEU)database.For eczema and autoimmune diseases,genetic instrument variants(GIVs)were identified according to the significant difference(P<5×10−8).Causal effect estimates were generated using the inverse‐variance weighted(IVW)method.MR Egger,maximum likelihood,MR-PRESSO,and MR-RAPS methods were used for alternative analyses.Sensitivity tests,including heterogeneity,horizontal pleiotropy,and leave-one-out analyses,were performed.Finally,reverse causality was assessed.Results:Genetic susceptibility to eczema was associated with an increased risk of Crohn’s disease(OR=1.444,95%CI 1.199 to 1.738,P<0.001)and ulcerative colitis(OR=1.002,95%CI 1.001 to 1.003,P=0.002).However,no causal relationship was found for the other 6 autoimmune diseases,including systemic lupus erythematosus(SLE)(OR=0.932,P=0.401),bullous pemphigoid(BP)(OR=1.191,P=0.642),vitiligo(OR=1.000,P=0.327),multiple sclerosis(MS)(OR=1.000,P=0.965),ankylosing spondylitis(AS)(OR=1.001,P=0.121),rheumatoid arthritis(RA)(OR=1.000,P=0.460).Additionally,no reverse causal relationship was found between autoimmune diseases and eczema.Conclusion:Eczema is associated with an increased risk of Crohn’s disease and ulcerative colitis.No causal relationship is found between eczema and SLE,MS,AS,RA,BP,or vitiligo.
基金This work was supported by the National Natural Science Foundation of China(12171451,72091212).
文摘Mendelian randomization(MR)is widely used in causal mediation analysis to control unmeasured confounding effects,which is valid under some strong assumptions.It is thus of great interest to assess the impact of violations of these MR assumptions through sensitivity analysis.Sensitivity analyses have been conducted for simple MR-based causal average effect analyses,but they are not available for MR-based mediation analysis studies,and we aim to fill this gap in this paper.We propose to use two sensitivity parameters to quantify the effect due to the deviation of the IV assumptions.With these two sensitivity parameters,we derive consistent indirect causal effect estimators and establish their asymptotic propersties.Our theoretical results can be used in MR-based mediation analysis to study the impact of violations of MR as-sumptions.The finite sample performance of the proposed method is illustrated through simulation studies,sensitivity ana-lysis,and application to a real genome-wide association study.
基金supported by the Natural Science Foundation of Hunan Province,China(2024JJ7627).
文摘Objective:Gut microbiota(GM)and blood metabolites are associated with the development of urticaria,yet their specific causal relationships in East Asian populations remain unclear.This study aims to elucidate the causal and mediating relationships among GM,blood metabolites,and urticaria in East Asians using Mendelian randomization(MR)analysis.Methods:Summary-level statistics for 500 GM taxa,112 blood metabolites,and urticaria were obtained from publicly available Genome-Wide Association Studies(GWAS)datasets.Bidirectional MR analyses were performed to examine causal associations among the GM,blood metabolites,and urticaria.The inverse variance weighted(IVW)method served as the primary analytical approach,supplemented by MR-Egger,weighted median,simple mode,and weighted mode methods.Sensitivity analyses included heterogeneity tests,horizontal pleiotropy assessments,and leave-one-out analyses.Mediation analysis was conducted to evaluate the potential mediating effects of blood metabolites on the causal pathways between GM and urticaria.Results:MR analyses identified 12 GM taxa exhibiting significant causal effects on urticaria susceptibility.Nine taxa,such as MF0017_galactose_degradation(OR=1.461,95%CI 1.098 to 1.944,P=0.009),were associated with increased urticaria risk.Three taxa,such as MF0001_arabinoxylan_degradation(OR=0.846,95%CI 0.737 to 0.973,P=0.019),showed protective effects with increased abundance.Additionally,6 blood metabolites demonstrated causal associations with urticaria.Notably,the risk of developing urticaria increases with rising fasting plasma glucose(FPG)levels(OR=1.971,95%CI 1.089 to 3.567,P=0.025).Mediation analysis further demonstrated that FPG partially mediated the protective effect of MF0001_arabinoxylan_degradation on urticaria,accounting for 11.30%of the total effect.Conclusion:This study has delineated specific GM taxa and blood metabolites that hold causal relevance to urticaria in East Asian populations.Notably,arabinogalactan degradation potentially mitigates urticaria risk via reducing FPG concentrations,offering genetic evidence to support therapeutic strategies targeting GM modulation and glucose regulation.
文摘Creutzfeldt-Jakob disease(CJD)is a rare neurodegenerative disorder characterized by abnormalities in the prion protein(PrP),the most common form of human prion disease.Although Genome-Wide Association Studies(GWAS)have identified numerous risk genes for CJD,the mechanisms underlying these risk loci remain poorly understood.This study aims to elucidate novel genetically prioritized candidate proteins associated with CJD in the human brain through an integrative analytical pipeline.Utilizing datasets from Protein Quantitative Trait Loci(pQTL)(NpQTL1=152,NpQTL2=376),expression QTL(eQTL)(N=452),and the CJD GWAS(NCJD=4110,NControls=13569),we implemented a systematic analytical pipeline.This pipeline included Proteome-Wide Association Study(PWAS),Mendelian randomization(MR),Bayesian colocalization,and Transcriptome-Wide Association Study(TWAS)to identify novel genetically prioritized candidate proteins implicated in CJD pathogenesis within the brain.Through PWAS,we identified that the altered abundance of six brain proteins was significantly associated with CJD.Two genes,STX6 and PDIA4,were established as lead causal genes for CJD,supported by robust evidence(False Discovery Rate<0.05 in MR analysis;PP4/(PP3+PP4)≥0.75 in Bayesian colocalization).Specifically,elevated levels of STX6 and PDIA4 were associated with an increased risk of CJD.Additionally,TWAS demonstrated that STX6 and PDIA4 were associated with CJD at the transcriptional level.
文摘OBJECTIVE To investigate the intervention effects of tissue-bone homeostasis manipulation(TBHM)on peripatellar biomechanical parameters and knee joint function in knee osteoarthritis(KOA)patients.METHODS Sixty patients with KOA(Kellgren-Lawrence gradeⅡ-Ⅲ)were recruited from the Acupuncture-Moxibustion Rehabilitation Department,Anhui University of Chinese Medicine between October 2024 and May 2025.Participants were randomized into a TBHM group(n=30)or a transcutaneous electrical neuromuscular stimulation(TENS)group(n=30).Using two-way repeated measures ANOVA,biomechanical indicators,including rectus femoris tension,vastus medialis tension,vastus lateralis tension,patellar ligament tension,lateral patellar displacement(LPD),medial patellar displacement(MPD),normalized patellar mobility(LPD/patellar width[PW],MPD/PW),knee flexion range of motion,and functional indicators,including KOOS subscales,time up and go test(TUGT),were compared between groups at baseline and after 6 weeks of intervention.RESULTS After intervention,all biomechanical and knee joint function indicators in the TBHM group were significantly improved(P<0.05,P<0.01),while only the vastus medialis tension,TUGT and KOOS Pain,ADL and QoL scores in the control group were significantly improved(P<0.01).The improvement amplitudes of biomechanical indicators in the TBHM group,including rectus femoris tension,vastus lateralis tension,patellar ligament tension,MPD/PW,LPD/PW and knee flexion range of motion were better than those in the control group(P<0.05,P<0.01).In the functional evaluation,the interaction effects of the TBHM group in all dimensions of the KOOS score and TUGT were statistically significant(P<0.05,P<0.01).Post-hoc simple effect analysis confirmed that there were significant differences in the above indicators between the two groups after intervention(P<0.05),and all indicators showed a significant main effect of time(P<0.01),suggesting that the intervention measures had continuous and cumulative curative effects.CONCLUSION TBHM effectively improves joint function and quality of life in KOA patients by restoring dynamic equilibrium in soft tissue tension and patellar mobility,ultimately achieving the therapeutic goal of concurrent tissue-bone management.
基金supported by the National Natural Science Foundation of China(Grant No.11671145)the Science and Technology Commission of Shanghai Municipality(Grant No.18dz2271000).
文摘In this paper,large deviations principle(LDP)and moderate deviations principle(MDP)of record numbers in random walks are studied under certain conditions.The results show that the rate functions of LDP and MDP are different from those of weak record numbers,which are interesting complements of the conclusions by Li and Yao[1].
基金supported by Doctoral Scientific Research Starting Foundation of Jingdezhen Ceramic University(Grant No.102/01003002031)Re-accompanying Funding Project of Academic Achievements of Jingdezhen Ceramic University(Grant Nos.215/20506277,215/20506341)。
文摘The complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space is studied.By moment inequality and truncation methods,we establish the equivalent conditions of complete convergence for weighted sums of sequences of independent,identically distributed random variables under sublinear expectation space.The results complement the corresponding results in probability space to those for sequences of independent,identically distributed random variables under sublinear expectation space.
基金supported by the National Social Science Fundation(Grant No.21BTJ040)the Project of Outstanding Young People in University of Anhui Province(Grant Nos.2023AH020037,SLXY2024A001).
文摘In this paper,by utilizing the Marcinkiewicz-Zygmund inequality and Rosenthal-type inequality of negatively superadditive dependent(NSD)random arrays and truncated method,we investigate the complete f-moment convergence of NSD random variables.We establish and improve a general result on the complete f-moment convergence for Sung’s type randomly weighted sums of NSD random variables under some general assumptions.As an application,we show the complete consistency for the randomly weighted estimator in a nonparametric regression model based on NSD errors.
文摘Missiles provide long-range precision strike capabilities and have become a cornerstone of modern warfare.The contrail clouds formed by missile during their active flight phase present significant chal-lenges to high-altitude environmental observation and target detection and tracking.Existing studies primarily focus on specific airspace regions,leaving critical gaps in understanding the effects of long dispersion times,wide altitude ranges,and variable atmospheric conditions on missile contrail clouds.To address these gaps,this article develops a numerical method based on the Lagrangian random walk model,which incorporates various velocity variation terms,including particle velocity caused by the difference of wind field,by the thermal motion of local gas molecules and by random collisions between contrail cloud particles to capture the influence of environmental wind fields,atmospheric conditions,and particle concentrations on the motion of contrail cloud particles.A general coordinate system aligned with the missile's flight trajectory is employed to represent particle distribution characteristics.The proposed method is in good agreement with the conducted experiments as well as with the available numerical simulations.The results demonstrate that the proposed model effectively simulates the dispersion state of contrail clouds,accurately reflecting the impact of large-scale wind field variations and altitude changes with high computational efficiency.Additionally,simulation results indicate that the increased distance between gas molecules in rarefied environments facilitates enhanced particle dispersion,while larger particles exhibit a faster dispersion rate due to their greater mass.
基金Project(52178402) supported by the National Natural Science Foundation of China。
文摘This paper proposes a longitudinal vulnerability-based analysis method to evaluate the impact of foundation pit excavation on shield tunnels,accounting for geological uncertainties.First,the shield tunnel is modeled as an Euler Bernoulli beam resting on the Pasternak foundation incorporating variability in subgrade parameters along the tunnel’s length.A random analysis method using random field theory is introduced to evaluate the tunnel’s longitudinal responses to excavation.Next,a risk assessment index system is established.The normalized relative depth between the excavation and the shield tunnel is used as a risk index,while the maximum longitudinal deformation,the maximum circumferential opening,and the maximum longitudinal bending moment serve as performance indicators.Based on these,a method for analyzing the longitudinal fragility of shield tunnels under excavation-induced disturbances is proposed.Finally,the technique is applied to a case study involving a foundation pit excavation above a shield tunnel,which is the primary application scenario of this method.Vulnerability curves for different performance indicators are derived,and the effects of tunnel stiffness and subgrade stiffness on the tunnel vulnerability are explored.The results reveal significant differences in vulnerability curves depending on the performance index used.Compared to the maximum circumferential opening and the maximum longitudinal bending moment,selecting the maximum longitudinal deformation as the control index better ensures the tunnel’s usability and safety under excavation disturbances.The longitudinal vulnerability of the shield tunnel nonlinearly decreases with the increase of the tunnel stiffness and subgrade stiffness,and the subgrade stiffness has a more pronounced effect.Parametric analyses suggest that actively reinforcing the substratum is more effective on reducing the risk of tunnel failure due to adjacent excavations than passive reinforcement of the tunnel structure.
基金supported by National Natural Science Foundation of China(Grant No.12432018,12372346)the Innovative Research Groups of the National Natural Science Foundation of China(Grant No.12221002).
文摘A typical Whipple shield consists of double-layered plates with a certain gap.The space debris impacts the outer plate and is broken into a debris cloud(shattered,molten,vaporized)with dispersed energy and momentum,which reduces the risk of penetrating the bulkhead.In the realm of hypervelocity impact,strain rate(>10^(5)s^(-1))effects are negligible,and fluid dynamics is employed to describe the impact process.Efficient numerical tools for precisely predicting the damage degree can greatly accelerate the design and optimization of advanced protective structures.Current hypervelocity impact research primarily focuses on the interaction between projectile and front plate and the movement of debris cloud.However,the damage mechanism of debris cloud impacts on rear plates-the critical threat component-remains underexplored owing to complex multi-physics processes and prohibitive computational costs.Existing approaches,ranging from semi-empirical equations to a machine learningbased ballistic limit prediction method,are constrained to binary penetration classification.Alternatively,the uneven data from experiments and simulations caused these methods to be ineffective when the projectile has irregular shapes and complicate flight attitude.Therefore,it is urgent to develop a new damage prediction method for predicting the rear plate damage,which can help to gain a deeper understanding of the damage mechanism.In this study,a machine learning(ML)method is developed to predict the damage distribution in the rear plate.Based on the unit velocity space,the discretized information of debris cloud and rear plate damage from rare simulation cases is used as input data for training the ML models,while the generalization ability for damage distribution prediction is tested by other simulation cases with different attack angles.The results demonstrate that the training and prediction accuracies using the Random Forest(RF)algorithm significantly surpass those using Artificial Neural Networks(ANNs)and Support Vector Machine(SVM).The RF-based model effectively identifies damage features in sparsely distributed debris cloud and cumulative effect.This study establishes an expandable new dataset that accommodates additional parameters to improve the prediction accuracy.Results demonstrate the model's ability to overcome data imbalance limitations through debris cloud features,enabling rapid and accurate rear plate damage prediction across wider scenarios with minimal data requirements.
基金National Natural Science Foundation of China(71690233,71971213,71901214)。
文摘Architecture framework has become an effective method recently to describe the system of systems(SoS)architecture,such as the United States(US)Department of Defense Architecture Framework Version 2.0(DoDAF2.0).As a viewpoint in DoDAF2.0,the operational viewpoint(OV)describes operational activities,nodes,and resource flows.The OV models are important for SoS architecture development.However,as the SoS complexity increases,constructing OV models with traditional methods exposes shortcomings,such as inefficient data collection and low modeling standards.Therefore,we propose an intelligent modeling method for five OV models,including operational resource flow OV-2,organizational relationships OV-4,operational activity hierarchy OV-5a,operational activities model OV-5b,and operational activity sequences OV-6c.The main idea of the method is to extract OV architecture data from text and generate interoperable OV models.First,we construct the OV meta model based on the DoDAF2.0 meta model(DM2).Second,OV architecture named entities is recognized from text based on the bidirectional long short-term memory and conditional random field(BiLSTM-CRF)model.And OV architecture relationships are collected with relationship extraction rules.Finally,we define the generation rules for OV models and develop an OV modeling tool.We use unmanned surface vehicles(USV)swarm target defense SoS architecture as a case to verify the feasibility and effectiveness of the intelligent modeling method.
文摘开放领域新词发现研究对于中文自然语言处理的性能提升有着重要的意义.利用条件随机场(condition random field,简称CRF)可对序列输入标注的特点,将新词发现问题转化为预测已分词词语边界是否为新词边界的问题.在对海量规模中文互联网语料进行分析挖掘的基础上,提出了一系列区分新词边界的统计特征,并采用CRF方法综合这些特征实现了开放领域新词发现的算法,同时比较了K-Means聚类、等频率、基于信息增益这3种离散化方法对新词发现结果的影响.通过在SogouT大规模中文语料库上的新词发现实验,验证了所提出的方法有较好的效果.
