Objectives:This systematic review and meta-analysis aimed to identify and synthesize the factors correlated with posttraumatic growth(PTG)in patients with colorectal cancer(CRC).Methods:PubMed,Web of Science,Embase,Ps...Objectives:This systematic review and meta-analysis aimed to identify and synthesize the factors correlated with posttraumatic growth(PTG)in patients with colorectal cancer(CRC).Methods:PubMed,Web of Science,Embase,PsycINFO,CINAHL,Cochrane Library,China National Knowledge Infrastructure(CNKI),Wanfang database,China Science and Technology Journal Database(VIP)and SinoMed were searched for studies that reported data on the correlated factors associated with PTG in patients with CRC from inception to September 3,2024.The methodological quality of the included studies was assessed via the Agency for Healthcare Research and Quality(AHRQ)methodology checklist and the Newcastle-Ottawa Scale(NOS).Pearson correlation coefficient(r)was utilized to indicate effect size.Meta-analysis was conducted in R Studio.Results:Thirty-one eligible studies encompassing 6,400 participants were included in this review.Correlated factors were identified to be significantly associated with PTG in patients with CRC including demographic factors:residential area(r=0.13),marital status(r=0.10),employment status(r=0.18),education level(r=0.19),income level(r=0.16);disease-related factors:time since surgery(r=0.17),stoma-related complications(r=0.14),health-promoting behavior(r=0.46),and sexual function(r=0.17);psychosocial factors:confrontation coping(r=0.68),avoidance coping(r=-0.65),deliberate rumination(r=0.56),social support(r=0.47),family function(r=0.50),resilience(r=0.53),selfefficacy(r=0.91),self-compassion(r=-0.32),psychosocial adjustment(r=0.39),gratitude(r=0.45),stigma(r=-0.65),self-perceived burden(r=-0.31),fear of cancer recurrence(r=-0.45);and quality of life(r=0.32).Conclusions:This meta-analysis identified 23 factors associated with PTG in CRC patients.Medical workers can combine those relevant factors from the perspective of positive psychology,further explore the occurrence and development mechanism of PTG,and establish targeted interventions to promote PTG.展开更多
This paper addresses the computational problem of fixed-interval smoothing state estimation in linear time-varying Gaussian stochastic systems.A new fixed-interval Kalman smoothing algorithm is proposed,and the corres...This paper addresses the computational problem of fixed-interval smoothing state estimation in linear time-varying Gaussian stochastic systems.A new fixed-interval Kalman smoothing algorithm is proposed,and the corresponding form of the smoother is derived.The method is able to accommodate situations where process and measurement noises are correlated,a limitation often encountered in conventional approaches.The Kalman smoothing problem discussed in this paper can be reformulated as an equivalent constrained optimization problem,where the solution corresponds to a set of linear equations defined by a specific co-efficient matrix.Through multiple permutations,the co-efficient matrix of linear equations is transformed into a block tridiagonal form,and then both sides of the linear system are multiplied by the inverse of the co-efficient matrix.This approach is based on the transformation of linear systems described in the SPIKE algorithm and is particularly well-suited for large-scale sparse block tridiagonal matrix structures.It enables efficient,parallel,and flexible solutions while maintaining a certain degree of block diagonal dominance.Compared to directly solving block tridiagonal co-efficient matrices,this method demonstrates appreciable advantages in terms of numerical stability and computational efficiency.Consequently,the new smoothing algorithm yields a new smoother that features fewer constraints and broader applicability than traditional methods.The estimates,such as smoothed state,covariance,and cross-covariance,are essential for fields,such as system identification,navigation,guidance,and control.Finally,the effectiveness of the proposed smoothing algorithm and smoother is validated through numerical simulations.展开更多
Objective Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health.Analysis of these mixture exposures presents several key challenges for environmental epidemio...Objective Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health.Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment,including high dimensionality,correlated exposure,and subtle individual effects.Methods We proposed a novel statistical approach,the generalized functional linear model(GFLM),to analyze the health effects of exposure mixtures.GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation.The robustness and efficiency was evaluated under various scenarios through extensive simulation studies.Results We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey(NHANES).In the first application,we examined the effects of 37 nutrients on BMI(2011–2016 cycles).The GFLM identified a significant mixture effect,with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI,respectively.For the second application,we investigated the association between four pre-and perfluoroalkyl substances(PFAS)and gout risk(2007–2018 cycles).Unlike traditional methods,the GFLM indicated no significant association,demonstrating its robustness to multicollinearity.Conclusion GFLM framework is a powerful tool for mixture exposure analysis,offering improved handling of correlated exposures and interpretable results.It demonstrates robust performance across various scenarios and real-world applications,advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.展开更多
This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer mult...This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer multiple of the state update period. The focus is on scenarios where the correlations among Measurement Noises(MNs) from different sensors are unknown. Firstly, a non-augmented local estimator that applies to sampling cases is designed to provide unbiased Local Estimates(LEs) at the fusion points. Subsequently, a measurement-equivalent approach is then developed to parameterize the correlation structure between LEs and reformulate LEs into a unified form, thereby constraining the correlations arising from MNs to an admissible range. Simultaneously, a family of upper bounds on the joint error covariance matrix of LEs is derived based on the constrained correlations, avoiding the need to calculate the exact error cross-covariance matrix of LEs. Finally, a sequential fusion estimator is proposed in the sense of Weighted Minimum Mean Square Error(WMMSE), and it is proven to be unbiased, consistent, and more accurate than the well-known covariance intersection method. Simulation results illustrate the effectiveness of the proposed algorithm by highlighting improvements in consistency and accuracy.展开更多
In moiré-patterned van der Waals structures of transition metal dichalcogenides,correlated insulators can form under integer and fractional fillings,whose transport properties are governed by various quasiparticl...In moiré-patterned van der Waals structures of transition metal dichalcogenides,correlated insulators can form under integer and fractional fillings,whose transport properties are governed by various quasiparticle excitations including holons,doublons and interlayer exciton insulators.Here we theoretically investigate the nearest-neighbor inter-site hoppings of holons and interlayer exciton insulators.Our analysis indicates that these hopping strengths are significantly enhanced compared to that of a single carrier.The underlying mechanism can be attributed to the strong Coulomb interaction between carriers at different sites.For the interlayer exciton insulator consisting of a holon and a carrier in different layers,we have also obtained its effective Bohr radius and energy splitting between the ground and the first-excited states.展开更多
The construction of polar codes in corre-lated block fading channels is still an open issue to be solved.In this paper,to explicitly reveal the impact of correlation on error performance of polar coded diver-sity comm...The construction of polar codes in corre-lated block fading channels is still an open issue to be solved.In this paper,to explicitly reveal the impact of correlation on error performance of polar coded diver-sity communication systems,an integrated framework has been established to analyze the theoretical error performance of polar codes in correlated block fading channels.First,the upper bound on error probabil-ity of polarized channels is derived based on split po-lar spectrum,which is fully determined by covariance channel matrix as well as the block-wise weight distri-bution of the corresponding polar subcode.Further,to facilitate practical implementations,we design a con-struction metric named polarized correlation weight(PCW)to generate polar codes in correlated block fad-ing channels.Finally,simulation results on block error rate indicate that the proposed metric can exhibit both diversity gain and coding gain compared to the con-ventional methods under successive cancellation de-coding.展开更多
We develop a numerical method for the time evolution of Gaussian wave packets on flat-band lattices in the presence of correlated disorder.To achieve this,we introduce a method to generate random on-site energies with...We develop a numerical method for the time evolution of Gaussian wave packets on flat-band lattices in the presence of correlated disorder.To achieve this,we introduce a method to generate random on-site energies with prescribed correlations.We verify this method with a one-dimensional(1D)cross-stitch model,and find good agreement with analytical results obtained from the disorder-dressed evolution equations.This allows us to reproduce previous findings,that disorder can mobilize 1D flat-band states which would otherwise remain localized.As explained by the corresponding disorder-dressed evolution equations,such mobilization requires an asymmetric disorder-induced coupling to dispersive bands,a condition that is generically not fulfilled when the flat-band is resonant with the dispersive bands at a Dirac point-like crossing.We exemplify this with the 1D Lieb lattice.While analytical expressions are not available for the two-dimensional(2D)system due to its complexity,we extend the numerical method to the 2D a–T3 model,and find that the initial flat-band wave packet preserves its localization when a=0,regardless of disorder and intersections.However,when a̸=0,the wave packet shifts in real space.We interpret this as a Berry phase controlled,disorder-induced wave-packet mobilization.In addition,we present density functional theory calculations of candidate materials,specifically Hg1−xCdxTe.The flat-band emerges near the G point(α=0)in the Brillouin zone.展开更多
Mottness is at the heart of the essential physics in a strongly correlated system as many novel quantum phenomena occur in the metallic phase near the Mott metal–insulator transition. We investigate the Mott transiti...Mottness is at the heart of the essential physics in a strongly correlated system as many novel quantum phenomena occur in the metallic phase near the Mott metal–insulator transition. We investigate the Mott transition in a Hubbard model by using the dynamical mean-field theory and introduce the local quantum state fidelity to depict the Mott metal–insulator transition. The local quantum state fidelity provides a convenient approach to determining the critical point of the Mott transition. Additionally, it presents a consistent description of the two distinct forms of the Mott transition points.展开更多
This letter proposes a sliced-gated-convolutional neural network with belief propagation(SGCNN-BP) architecture for decoding long codes under correlated noise. The basic idea of SGCNNBP is using Neural Networks(NN) to...This letter proposes a sliced-gated-convolutional neural network with belief propagation(SGCNN-BP) architecture for decoding long codes under correlated noise. The basic idea of SGCNNBP is using Neural Networks(NN) to transform the correlated noise into white noise, setting up the optimal condition for a standard BP decoder that takes the output from the NN. A gate-controlled neuron is used to regulate information flow and an optional operation—slicing is adopted to reduce parameters and lower training complexity. Simulation results show that SGCNN-BP has much better performance(with the largest gap being 5dB improvement) than a single BP decoder and achieves a nearly 1dB improvement compared to Fully Convolutional Networks(FCN).展开更多
A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establ...A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establish three lemmas:normal corre-lation,equivalent pricing and equivalent profit,which can guarantee to turn our model into a model with insider knowing full information.Then we investigate the impact of the two correlated signals on the market equilibrium consisting of optimal insider trading strategy and semi-strong pricing rule.It shows that in the equilibrium,(1)the market depth is constant over time;(2)if the two noisy signals are not linerly correlated,then all private information of the insider is incorporated into prices in the end while the whole information on the asset value can not incorporated into prices in the end;(3)if the two noisy signals are linear correlated such that the insider can infer the whole information of the asset value,then our model turns into a model with insider knowing full information;(4)if the two noisy signals are the same then the total ex ant profit of the insider is increasing with the noise decreasing,while down to O as the noise going up to infinity;(5)if the two noisy signals are not linear correlated then with one noisy signal fixed,the total ex ante profit of the insider is single-peaked with a unique minimum with respect to the other noisy signal value,and furthermore as the noisy value going to O it gets its maximum,the profit in the case that the real value is observed.展开更多
Different from the previous qualitative analysis of linear systems in time and frequency domains, the method for describing nonlinear systems quantitatively is proposed based on correlated dimensions. Nonlinear dynami...Different from the previous qualitative analysis of linear systems in time and frequency domains, the method for describing nonlinear systems quantitatively is proposed based on correlated dimensions. Nonlinear dynamics theory is used to analyze the pressure data of a contrarotating axial flow fan. The delay time is 18 and the embedded dimension varies from 1 to 25 through phase-space reconstruction. In addition, the correlated dimensions are calculated before and after stalling. The results show that the correlated dimensions drop from 1. 428 before stalling to 1. 198 after stalling, so they are sensitive to the stalling signal of the fan and can be used as a characteristic quantity for the judging of the fan stalling.展开更多
In structural simulation and design,an accurate computational model directly determines the effectiveness of performance evaluation.To establish a high-fidelity dynamic model of a complex assembled structure,a Hierarc...In structural simulation and design,an accurate computational model directly determines the effectiveness of performance evaluation.To establish a high-fidelity dynamic model of a complex assembled structure,a Hierarchical Model Updating Strategy(HMUS)is developed for Finite Element(FE)model updating with regard to uncorrelated modes.The principle of HMUS is first elaborated by integrating hierarchical modeling concept,model updating technology with proper uncorrelated mode treatment,and parametric modeling.In the developed strategy,the correct correlated mode pairs amongst the uncorrelated modes are identified by an error minimization procedure.The proposed updating technique is validated by the dynamic FE model updating of a simple fixed–fixed beam.The proposed HMUS is then applied to the FE model updating of an aeroengine stator system(casings)to demonstrate its effectiveness.Our studies reveal that(A)parametric modeling technique is able to build an efficient equivalent model by simplifying complex structure in geometry while ensuring the consistency of mechanical characteristics;(B)the developed model updating technique efficiently processes the uncorrelated modes and precisely identifies correct Correlated Mode Pairs(CMPs)between FE model and experiment;(C)the proposed HMUS is accurate and efficient in the FE model updating of complex assembled structures such as aeroengine casings with large-scale model,complex geometry,high-nonlinearity and numerous parameters;(D)it is appropriate to update a complex structural FE model parameterized.The efforts of this study provide an efficient updating strategy for the dynamic model updating of complex assembled structures with experimental test data,which is promising to promote the precision and feasibility of simulation-based design optimization and performance evaluation of complex structures.展开更多
The logistic growth model with correlated additive and multiplicative Gaussian white noise is used to anedyze tumor cell population. The effects of perfectly correlated and anti-correlated noise on the stationary prop...The logistic growth model with correlated additive and multiplicative Gaussian white noise is used to anedyze tumor cell population. The effects of perfectly correlated and anti-correlated noise on the stationary properties of tumor cell population are studied. As in both cases the diffusion coefficient has zero point in real number field, some special features of the system are arisen. It is found that in cause tumor cell extinction. In the perfectly anti-correlated tumor cell population exhibit two extrema. both cases, the increase of the multiplicative noise intensity case, the stationary probability distribution as a function of展开更多
This article considers a risk model as in Yuen et al. （2002）. Under this model the two claim number processes are correlated. Claim occurrence of both classes relate to Poisson and Erlang processes. The formulae is ...This article considers a risk model as in Yuen et al. （2002）. Under this model the two claim number processes are correlated. Claim occurrence of both classes relate to Poisson and Erlang processes. The formulae is derived for the distribution of the surplus immediately before ruin, for the distribution of the surplus immediately after ruin and the joint distribution of the surplus immediately before and after ruin. The asymptotic property of these ruin functions is also investigated.展开更多
In order to suit the condition that the wave uplift is correlated with the horizontal wave load acting on a vertical breakwater, a generally used method for determining the reliability index β of the breakwater, i.e....In order to suit the condition that the wave uplift is correlated with the horizontal wave load acting on a vertical breakwater, a generally used method for determining the reliability index β of the breakwater, i.e. the Hasofer-Lind method, is extended in a generalized stochastic space for correlative variables. The computational results for a caisson breakwater indicate that the value of β for the case of correlated variables is obviously smaller than that for the case of independent variables.展开更多
Many complex traits are highly correlated rather than independent. By taking the correlation structure of multiple traits into account, joint association analyses can achieve both higher statistical power and more acc...Many complex traits are highly correlated rather than independent. By taking the correlation structure of multiple traits into account, joint association analyses can achieve both higher statistical power and more accurate estimation. To develop a statistical approach to joint association analysis that includes allele detection and genetic effect estimation, we combined multivariate partial least squares regression with variable selection strategies and selected the optimal model using the Bayesian Information Criterion(BIC). We then performed extensive simulations under varying heritabilities and sample sizes to compare the performance achieved using our method with those obtained by single-trait multilocus methods. Joint association analysis has measurable advantages over single-trait methods, as it exhibits superior gene detection power, especially for pleiotropic genes. Sample size, heritability,polymorphic information content(PIC), and magnitude of gene effects influence the statistical power, accuracy and precision of effect estimation by the joint association analysis.展开更多
Based on the major gene and polygene mixed inheritance model for multiple correlated quantitative traits, the authors proposed a new joint segregation analysis method of major gene controlling multiple correlated quan...Based on the major gene and polygene mixed inheritance model for multiple correlated quantitative traits, the authors proposed a new joint segregation analysis method of major gene controlling multiple correlated quantitative traits, which include major gene detection and its effect and variation estimation. The effect and variation of major gene are estimated by the maximum likelihood method implemented via expectation-maximization （EM） algorithm. Major gene is tested with the likelihood ratio （LR） test statistic. Extensive simulation studies showed that joint analysis not only increases the statistical power of major gene detection but also improves the precision and accuracy of major gene effect estimates. An example of the plant height and the number of tiller of F2 population in rice cross Duonieai x Zhonghua 11 was used in the illustration. The results indicated that the genetic difference of these two traits in this cross refers to only one pleiotropic major gene. The additive effect and dominance effect of the major gene are estimated as -21.3 and 40.6 cm on plant height, and 22.7 and -25.3 on number of tiller, respectively. The major gene shows overdominance for plant height and close to complete dominance for number of tillers.展开更多
When Kalman filter is used in the estimation of Vasicek term structure of interest rates,it is usual to assume that the measurement noise is uncorrelated.Study results are more favorable to the assumption of correlate...When Kalman filter is used in the estimation of Vasicek term structure of interest rates,it is usual to assume that the measurement noise is uncorrelated.Study results are more favorable to the assumption of correlated measurement noise.An augmented state Kalman filter form for Vasicek model is proposed to optimally estimate the unobservable state variable with the assumption of correlated measurement noise.Empirical results indicate that the model with sequentially correlated measurement noise can more accurately describe the dynamics of the term structure of interest rates.展开更多
Free space optical(FSO) communication system with differential signaling possesses the advantage of requiring no channel state information and avoiding computational load or link throughput reduction compared to the s...Free space optical(FSO) communication system with differential signaling possesses the advantage of requiring no channel state information and avoiding computational load or link throughput reduction compared to the systems with conventional receivers. In this work, we investigate bit error rate(BER) performance of this system over partially and fully correlated atmospheric turbulence fading. In order to conduct the above analysis, we obtain a probability density functions(PDF) of the channel fading on the differential signals and derive our instantaneous BER using differential signaling scheme. Based on these results, we develop two closed-form mathematical expressions for the average BER under fully correlated and partially correlated fading in the convergent infinite series confirmed by Cauchy’s ratio test. The accuracy of the derived BER expressions is demonstrated by the Monte Carlo simulations, and the analyses for the effects of the system parameters on the BER performance are provided.展开更多
In this paper,a new correlated covariance matrix for Multi-Input Multi-Output(MIMO)radar is proposed,which has lower Side Lobe Levels(SLLs)compared to the new covariance matrix designs and the well-known multi-antenna...In this paper,a new correlated covariance matrix for Multi-Input Multi-Output(MIMO)radar is proposed,which has lower Side Lobe Levels(SLLs)compared to the new covariance matrix designs and the well-known multi-antenna radar designs including phased-array,MIMO radar and phased-MIMO radar schemes.It is shown that Binary Phased-Shift Keying(BPSK)waveforms that have constant envelope can be used in a closed-form to realize the proposed covariance matrix.Therefore,there is no need to deploy different types of radio amplifiers in the transmitter which will reduce the cost,considerably.The proposed design allows the same transmit power from each antenna in contrast to the phased-MIMO radar.Moreover,the proposed covariance matrix is full-rank and has the same capability as MIMO radar to identify more targets,simultaneously.Performance of the proposed transmit covariance matrix including receive beampattern and output Signal-to-Interference plus Noise Ratio(SINR)is simulated,which validates analytical results.展开更多
基金supported by the‘Double First-Class’Construction Specialized Discipline Project at Zhejiang University(No HL2024012).
文摘Objectives:This systematic review and meta-analysis aimed to identify and synthesize the factors correlated with posttraumatic growth(PTG)in patients with colorectal cancer(CRC).Methods:PubMed,Web of Science,Embase,PsycINFO,CINAHL,Cochrane Library,China National Knowledge Infrastructure(CNKI),Wanfang database,China Science and Technology Journal Database(VIP)and SinoMed were searched for studies that reported data on the correlated factors associated with PTG in patients with CRC from inception to September 3,2024.The methodological quality of the included studies was assessed via the Agency for Healthcare Research and Quality(AHRQ)methodology checklist and the Newcastle-Ottawa Scale(NOS).Pearson correlation coefficient(r)was utilized to indicate effect size.Meta-analysis was conducted in R Studio.Results:Thirty-one eligible studies encompassing 6,400 participants were included in this review.Correlated factors were identified to be significantly associated with PTG in patients with CRC including demographic factors:residential area(r=0.13),marital status(r=0.10),employment status(r=0.18),education level(r=0.19),income level(r=0.16);disease-related factors:time since surgery(r=0.17),stoma-related complications(r=0.14),health-promoting behavior(r=0.46),and sexual function(r=0.17);psychosocial factors:confrontation coping(r=0.68),avoidance coping(r=-0.65),deliberate rumination(r=0.56),social support(r=0.47),family function(r=0.50),resilience(r=0.53),selfefficacy(r=0.91),self-compassion(r=-0.32),psychosocial adjustment(r=0.39),gratitude(r=0.45),stigma(r=-0.65),self-perceived burden(r=-0.31),fear of cancer recurrence(r=-0.45);and quality of life(r=0.32).Conclusions:This meta-analysis identified 23 factors associated with PTG in CRC patients.Medical workers can combine those relevant factors from the perspective of positive psychology,further explore the occurrence and development mechanism of PTG,and establish targeted interventions to promote PTG.
文摘This paper addresses the computational problem of fixed-interval smoothing state estimation in linear time-varying Gaussian stochastic systems.A new fixed-interval Kalman smoothing algorithm is proposed,and the corresponding form of the smoother is derived.The method is able to accommodate situations where process and measurement noises are correlated,a limitation often encountered in conventional approaches.The Kalman smoothing problem discussed in this paper can be reformulated as an equivalent constrained optimization problem,where the solution corresponds to a set of linear equations defined by a specific co-efficient matrix.Through multiple permutations,the co-efficient matrix of linear equations is transformed into a block tridiagonal form,and then both sides of the linear system are multiplied by the inverse of the co-efficient matrix.This approach is based on the transformation of linear systems described in the SPIKE algorithm and is particularly well-suited for large-scale sparse block tridiagonal matrix structures.It enables efficient,parallel,and flexible solutions while maintaining a certain degree of block diagonal dominance.Compared to directly solving block tridiagonal co-efficient matrices,this method demonstrates appreciable advantages in terms of numerical stability and computational efficiency.Consequently,the new smoothing algorithm yields a new smoother that features fewer constraints and broader applicability than traditional methods.The estimates,such as smoothed state,covariance,and cross-covariance,are essential for fields,such as system identification,navigation,guidance,and control.Finally,the effectiveness of the proposed smoothing algorithm and smoother is validated through numerical simulations.
基金supported in part by the Young Scientists Fund of the National Natural Science Foundation of China(Grant Nos.82304253)(and 82273709)the Foundation for Young Talents in Higher Education of Guangdong Province(Grant No.2022KQNCX021)the PhD Starting Project of Guangdong Medical University(Grant No.GDMUB2022054).
文摘Objective Humans are exposed to complex mixtures of environmental chemicals and other factors that can affect their health.Analysis of these mixture exposures presents several key challenges for environmental epidemiology and risk assessment,including high dimensionality,correlated exposure,and subtle individual effects.Methods We proposed a novel statistical approach,the generalized functional linear model(GFLM),to analyze the health effects of exposure mixtures.GFLM treats the effect of mixture exposures as a smooth function by reordering exposures based on specific mechanisms and capturing internal correlations to provide a meaningful estimation and interpretation.The robustness and efficiency was evaluated under various scenarios through extensive simulation studies.Results We applied the GFLM to two datasets from the National Health and Nutrition Examination Survey(NHANES).In the first application,we examined the effects of 37 nutrients on BMI(2011–2016 cycles).The GFLM identified a significant mixture effect,with fiber and fat emerging as the nutrients with the greatest negative and positive effects on BMI,respectively.For the second application,we investigated the association between four pre-and perfluoroalkyl substances(PFAS)and gout risk(2007–2018 cycles).Unlike traditional methods,the GFLM indicated no significant association,demonstrating its robustness to multicollinearity.Conclusion GFLM framework is a powerful tool for mixture exposure analysis,offering improved handling of correlated exposures and interpretable results.It demonstrates robust performance across various scenarios and real-world applications,advancing our understanding of complex environmental exposures and their health impacts on environmental epidemiology and toxicology.
基金supported by the National Natural Science Foundation of China (Nos. 62276204, 62203343)。
文摘This study investigates a consistent fusion algorithm for distributed multi-rate multi-sensor systems operating in feedback-memory configurations, where each sensor's sampling period is uniform and an integer multiple of the state update period. The focus is on scenarios where the correlations among Measurement Noises(MNs) from different sensors are unknown. Firstly, a non-augmented local estimator that applies to sampling cases is designed to provide unbiased Local Estimates(LEs) at the fusion points. Subsequently, a measurement-equivalent approach is then developed to parameterize the correlation structure between LEs and reformulate LEs into a unified form, thereby constraining the correlations arising from MNs to an admissible range. Simultaneously, a family of upper bounds on the joint error covariance matrix of LEs is derived based on the constrained correlations, avoiding the need to calculate the exact error cross-covariance matrix of LEs. Finally, a sequential fusion estimator is proposed in the sense of Weighted Minimum Mean Square Error(WMMSE), and it is proven to be unbiased, consistent, and more accurate than the well-known covariance intersection method. Simulation results illustrate the effectiveness of the proposed algorithm by highlighting improvements in consistency and accuracy.
基金support by the National Natural Sci-ence Foundation of China(Grant No.12274477)the De-partment of Science and Technology of Guangdong Provincein China(Grant No.2019QN01X061)。
文摘In moiré-patterned van der Waals structures of transition metal dichalcogenides,correlated insulators can form under integer and fractional fillings,whose transport properties are governed by various quasiparticle excitations including holons,doublons and interlayer exciton insulators.Here we theoretically investigate the nearest-neighbor inter-site hoppings of holons and interlayer exciton insulators.Our analysis indicates that these hopping strengths are significantly enhanced compared to that of a single carrier.The underlying mechanism can be attributed to the strong Coulomb interaction between carriers at different sites.For the interlayer exciton insulator consisting of a holon and a carrier in different layers,we have also obtained its effective Bohr radius and energy splitting between the ground and the first-excited states.
基金supported by National Natural Science Foundation of China(No.62471054).
文摘The construction of polar codes in corre-lated block fading channels is still an open issue to be solved.In this paper,to explicitly reveal the impact of correlation on error performance of polar coded diver-sity communication systems,an integrated framework has been established to analyze the theoretical error performance of polar codes in correlated block fading channels.First,the upper bound on error probabil-ity of polarized channels is derived based on split po-lar spectrum,which is fully determined by covariance channel matrix as well as the block-wise weight distri-bution of the corresponding polar subcode.Further,to facilitate practical implementations,we design a con-struction metric named polarized correlation weight(PCW)to generate polar codes in correlated block fad-ing channels.Finally,simulation results on block error rate indicate that the proposed metric can exhibit both diversity gain and coding gain compared to the con-ventional methods under successive cancellation de-coding.
基金the National Natural Sci-ence Foundation of China(Grant No.61988102)the Key Research and Development Program of Guangdong Province(Grant No.2019B090917007)+5 种基金the Science and Technology Planning Project of Guangdong Province(Grant No.2019B090909011)Q.L.acknowledges Guangzhou Basic and Applied Basic Research Project(Grant No.2023A04J0018)Z.L.acknowledges the support of fund-ing from Chinese Academy of Sciences E1Z1D10200 and E2Z2D10200from ZJ project 2021QN02X159 and from JSPS(Grant Nos.PE14052 and P16027)We gratefully ac-knowledge HZWTECH for providing computation facilities.Z.-X.H.was supported by the National Natural Science Foun-dation of China(Grant Nos.11974064 and 12147102)the Fundamental Research Funds for the Central Universities(Grant No.2020CDJQY-Z003).
文摘We develop a numerical method for the time evolution of Gaussian wave packets on flat-band lattices in the presence of correlated disorder.To achieve this,we introduce a method to generate random on-site energies with prescribed correlations.We verify this method with a one-dimensional(1D)cross-stitch model,and find good agreement with analytical results obtained from the disorder-dressed evolution equations.This allows us to reproduce previous findings,that disorder can mobilize 1D flat-band states which would otherwise remain localized.As explained by the corresponding disorder-dressed evolution equations,such mobilization requires an asymmetric disorder-induced coupling to dispersive bands,a condition that is generically not fulfilled when the flat-band is resonant with the dispersive bands at a Dirac point-like crossing.We exemplify this with the 1D Lieb lattice.While analytical expressions are not available for the two-dimensional(2D)system due to its complexity,we extend the numerical method to the 2D a–T3 model,and find that the initial flat-band wave packet preserves its localization when a=0,regardless of disorder and intersections.However,when a̸=0,the wave packet shifts in real space.We interpret this as a Berry phase controlled,disorder-induced wave-packet mobilization.In addition,we present density functional theory calculations of candidate materials,specifically Hg1−xCdxTe.The flat-band emerges near the G point(α=0)in the Brillouin zone.
基金Project supported by the Scientific Research Foundation for Youth Academic Talent of Inner Mongolia University (Grant No.1000023112101/010)the Fundamental Research Funds for the Central Universities of China (Grant No.JN200208)+2 种基金supported by the National Natural Science Foundation of China (Grant No.11474023)supported by the National Key Research and Development Program of China (Grant No.2021YFA1401803)the National Natural Science Foundation of China (Grant Nos.11974051 and 11734002)。
文摘Mottness is at the heart of the essential physics in a strongly correlated system as many novel quantum phenomena occur in the metallic phase near the Mott metal–insulator transition. We investigate the Mott transition in a Hubbard model by using the dynamical mean-field theory and introduce the local quantum state fidelity to depict the Mott metal–insulator transition. The local quantum state fidelity provides a convenient approach to determining the critical point of the Mott transition. Additionally, it presents a consistent description of the two distinct forms of the Mott transition points.
基金supported by Beijing Natural Science Foundation (L202003)。
文摘This letter proposes a sliced-gated-convolutional neural network with belief propagation(SGCNN-BP) architecture for decoding long codes under correlated noise. The basic idea of SGCNNBP is using Neural Networks(NN) to transform the correlated noise into white noise, setting up the optimal condition for a standard BP decoder that takes the output from the NN. A gate-controlled neuron is used to regulate information flow and an optional operation—slicing is adopted to reduce parameters and lower training complexity. Simulation results show that SGCNN-BP has much better performance(with the largest gap being 5dB improvement) than a single BP decoder and achieves a nearly 1dB improvement compared to Fully Convolutional Networks(FCN).
文摘A model of continuous-time insider trading in which a risk-neutral in-sider possesses two imperfect correlated signals of a risky asset is studied.By conditional expectation theory and filtering theory,we first establish three lemmas:normal corre-lation,equivalent pricing and equivalent profit,which can guarantee to turn our model into a model with insider knowing full information.Then we investigate the impact of the two correlated signals on the market equilibrium consisting of optimal insider trading strategy and semi-strong pricing rule.It shows that in the equilibrium,(1)the market depth is constant over time;(2)if the two noisy signals are not linerly correlated,then all private information of the insider is incorporated into prices in the end while the whole information on the asset value can not incorporated into prices in the end;(3)if the two noisy signals are linear correlated such that the insider can infer the whole information of the asset value,then our model turns into a model with insider knowing full information;(4)if the two noisy signals are the same then the total ex ant profit of the insider is increasing with the noise decreasing,while down to O as the noise going up to infinity;(5)if the two noisy signals are not linear correlated then with one noisy signal fixed,the total ex ante profit of the insider is single-peaked with a unique minimum with respect to the other noisy signal value,and furthermore as the noisy value going to O it gets its maximum,the profit in the case that the real value is observed.
基金Supported by the Natural Science Foundation of Jiangsu Province(BK2005018)the Graduate Research and Innovation Plan of Jiangsu Province(CX07B-061Z)~~
文摘Different from the previous qualitative analysis of linear systems in time and frequency domains, the method for describing nonlinear systems quantitatively is proposed based on correlated dimensions. Nonlinear dynamics theory is used to analyze the pressure data of a contrarotating axial flow fan. The delay time is 18 and the embedded dimension varies from 1 to 25 through phase-space reconstruction. In addition, the correlated dimensions are calculated before and after stalling. The results show that the correlated dimensions drop from 1. 428 before stalling to 1. 198 after stalling, so they are sensitive to the stalling signal of the fan and can be used as a characteristic quantity for the judging of the fan stalling.
基金co-supported by National Natural Science Foundation of China(No.51975124)Shanghai International Cooperation Project of One Belt and One Road of China(No.20110741700)Major Research Special Project of Aeroengine and Gas Turbine of China(No.J2019-IV-0016)。
文摘In structural simulation and design,an accurate computational model directly determines the effectiveness of performance evaluation.To establish a high-fidelity dynamic model of a complex assembled structure,a Hierarchical Model Updating Strategy(HMUS)is developed for Finite Element(FE)model updating with regard to uncorrelated modes.The principle of HMUS is first elaborated by integrating hierarchical modeling concept,model updating technology with proper uncorrelated mode treatment,and parametric modeling.In the developed strategy,the correct correlated mode pairs amongst the uncorrelated modes are identified by an error minimization procedure.The proposed updating technique is validated by the dynamic FE model updating of a simple fixed–fixed beam.The proposed HMUS is then applied to the FE model updating of an aeroengine stator system(casings)to demonstrate its effectiveness.Our studies reveal that(A)parametric modeling technique is able to build an efficient equivalent model by simplifying complex structure in geometry while ensuring the consistency of mechanical characteristics;(B)the developed model updating technique efficiently processes the uncorrelated modes and precisely identifies correct Correlated Mode Pairs(CMPs)between FE model and experiment;(C)the proposed HMUS is accurate and efficient in the FE model updating of complex assembled structures such as aeroengine casings with large-scale model,complex geometry,high-nonlinearity and numerous parameters;(D)it is appropriate to update a complex structural FE model parameterized.The efforts of this study provide an efficient updating strategy for the dynamic model updating of complex assembled structures with experimental test data,which is promising to promote the precision and feasibility of simulation-based design optimization and performance evaluation of complex structures.
基金Supported by the National Natural Science Foundation of China under Grant No. 11045004
文摘The logistic growth model with correlated additive and multiplicative Gaussian white noise is used to anedyze tumor cell population. The effects of perfectly correlated and anti-correlated noise on the stationary properties of tumor cell population are studied. As in both cases the diffusion coefficient has zero point in real number field, some special features of the system are arisen. It is found that in cause tumor cell extinction. In the perfectly anti-correlated tumor cell population exhibit two extrema. both cases, the increase of the multiplicative noise intensity case, the stationary probability distribution as a function of
基金This work was supported in part by the National Natural Science Foundation of China (10071058, 70273029) the Ministry of Education of China.
文摘This article considers a risk model as in Yuen et al. （2002）. Under this model the two claim number processes are correlated. Claim occurrence of both classes relate to Poisson and Erlang processes. The formulae is derived for the distribution of the surplus immediately before ruin, for the distribution of the surplus immediately after ruin and the joint distribution of the surplus immediately before and after ruin. The asymptotic property of these ruin functions is also investigated.
文摘In order to suit the condition that the wave uplift is correlated with the horizontal wave load acting on a vertical breakwater, a generally used method for determining the reliability index β of the breakwater, i.e. the Hasofer-Lind method, is extended in a generalized stochastic space for correlative variables. The computational results for a caisson breakwater indicate that the value of β for the case of correlated variables is obviously smaller than that for the case of independent variables.
基金supported by grants from the National Program on the Development of Basic Research (2011CB100100)the Priority Academic Program Development of Jiangsu Higher Education Institutions, the National Natural Science Foundations (31391632, 31200943, 31171187, and 91535103)+3 种基金the National High-tech R&D Program (863 Program) (2014AA10A601-5)the Natural Science Foundations of Jiangsu Province (BK20150010)the Natural Science Foundation of the Jiangsu Higher Education Institutions (14KJA210005)the Innovative Research Team of Universities in Jiangsu Province (KYLX_1352)
文摘Many complex traits are highly correlated rather than independent. By taking the correlation structure of multiple traits into account, joint association analyses can achieve both higher statistical power and more accurate estimation. To develop a statistical approach to joint association analysis that includes allele detection and genetic effect estimation, we combined multivariate partial least squares regression with variable selection strategies and selected the optimal model using the Bayesian Information Criterion(BIC). We then performed extensive simulations under varying heritabilities and sample sizes to compare the performance achieved using our method with those obtained by single-trait multilocus methods. Joint association analysis has measurable advantages over single-trait methods, as it exhibits superior gene detection power, especially for pleiotropic genes. Sample size, heritability,polymorphic information content(PIC), and magnitude of gene effects influence the statistical power, accuracy and precision of effect estimation by the joint association analysis.
基金This research was supported by the National Natural Science Foundation of China to Xu Chenwu （39900080, 30270724 and 30370758）.
文摘Based on the major gene and polygene mixed inheritance model for multiple correlated quantitative traits, the authors proposed a new joint segregation analysis method of major gene controlling multiple correlated quantitative traits, which include major gene detection and its effect and variation estimation. The effect and variation of major gene are estimated by the maximum likelihood method implemented via expectation-maximization （EM） algorithm. Major gene is tested with the likelihood ratio （LR） test statistic. Extensive simulation studies showed that joint analysis not only increases the statistical power of major gene detection but also improves the precision and accuracy of major gene effect estimates. An example of the plant height and the number of tiller of F2 population in rice cross Duonieai x Zhonghua 11 was used in the illustration. The results indicated that the genetic difference of these two traits in this cross refers to only one pleiotropic major gene. The additive effect and dominance effect of the major gene are estimated as -21.3 and 40.6 cm on plant height, and 22.7 and -25.3 on number of tiller, respectively. The major gene shows overdominance for plant height and close to complete dominance for number of tillers.
文摘When Kalman filter is used in the estimation of Vasicek term structure of interest rates,it is usual to assume that the measurement noise is uncorrelated.Study results are more favorable to the assumption of correlated measurement noise.An augmented state Kalman filter form for Vasicek model is proposed to optimally estimate the unobservable state variable with the assumption of correlated measurement noise.Empirical results indicate that the model with sequentially correlated measurement noise can more accurately describe the dynamics of the term structure of interest rates.
文摘Free space optical(FSO) communication system with differential signaling possesses the advantage of requiring no channel state information and avoiding computational load or link throughput reduction compared to the systems with conventional receivers. In this work, we investigate bit error rate(BER) performance of this system over partially and fully correlated atmospheric turbulence fading. In order to conduct the above analysis, we obtain a probability density functions(PDF) of the channel fading on the differential signals and derive our instantaneous BER using differential signaling scheme. Based on these results, we develop two closed-form mathematical expressions for the average BER under fully correlated and partially correlated fading in the convergent infinite series confirmed by Cauchy’s ratio test. The accuracy of the derived BER expressions is demonstrated by the Monte Carlo simulations, and the analyses for the effects of the system parameters on the BER performance are provided.
文摘In this paper,a new correlated covariance matrix for Multi-Input Multi-Output(MIMO)radar is proposed,which has lower Side Lobe Levels(SLLs)compared to the new covariance matrix designs and the well-known multi-antenna radar designs including phased-array,MIMO radar and phased-MIMO radar schemes.It is shown that Binary Phased-Shift Keying(BPSK)waveforms that have constant envelope can be used in a closed-form to realize the proposed covariance matrix.Therefore,there is no need to deploy different types of radio amplifiers in the transmitter which will reduce the cost,considerably.The proposed design allows the same transmit power from each antenna in contrast to the phased-MIMO radar.Moreover,the proposed covariance matrix is full-rank and has the same capability as MIMO radar to identify more targets,simultaneously.Performance of the proposed transmit covariance matrix including receive beampattern and output Signal-to-Interference plus Noise Ratio(SINR)is simulated,which validates analytical results.
