Square-root cubature Kalman filter (SCKF) is more effective for nonlinear state estimation than an unscented Kalman filter.In this paper,we study the design of nonlinear filters based on SCKF for the system with one s...Square-root cubature Kalman filter (SCKF) is more effective for nonlinear state estimation than an unscented Kalman filter.In this paper,we study the design of nonlinear filters based on SCKF for the system with one step noise correlation and abrupt state change.First,we give the SCKF that deals with the one step correlation between process and measurement noises,SCKF-CN in short.Second,we introduce the idea of a strong tracking filter to construct the adaptive square-root factor of the prediction error covariance with a fading factor,which makes SCKF-CN obtain outstanding tracking performance to the system with target maneuver or abrupt state change.Accordingly,the tracking performance of SCKF is greatly improved.A universal nonlinear estimator is proposed,which can not only deal with the conventional nonlinear filter problem with high dimensionality and correlated noises,but also achieve an excellent strong tracking performance towards the abrupt change of target state.Three simulation examples with a bearings-only tracking system are illustrated to verify the efficiency of the proposed algorithms.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
Background Cerebral venous sinus thrombosis （CVST） is a special form of stroke with multiple causes and risk factors. However, there are still a portion of cases with unknown reasons. The aim of this study was to in...Background Cerebral venous sinus thrombosis （CVST） is a special form of stroke with multiple causes and risk factors. However, there are still a portion of cases with unknown reasons. The aim of this study was to investigate the relationship between internal jugular vein （IJV） abnormalities and the development of CVST. Methods A total of 51 CVST patients and 30 healthy controls were enrolled. The diameter, the maximum velocity （Vmax） and the reflux time in bilateral IJVs were measured by color Doppler flow imaging （CDFI）. The paired t test was used to compare the numeric values between the bilateral IJVs. The Pearson chi-square test was used to evaluate the relationship between IJV abnormality and CVST, IJV abnormality and IJV reflux, respectively. Results Among the 51 CVST patients, 20 （39%） patients were with normal IJV and 31 （61%） patients were with abnormal IJV. The types of IJV abnormality included annulus stenosis 19 cases （61%）, hypoplasia 9 cases （29%）, thrombosis 2 cases （7%） and anomalous valve 1 case （3%）. In patients with unilateral IJV abnormality, the minimum diameter of the IJV on the lesion side was significantly smaller than that of the contralateral side （P 〈0.0001）. When compared with contralateral side, the Vmax of the lesion side with unilateral annulus stenosis was significant higher, however, it was obvious lower in patients with unilateral hypoplasia （P 〈0.05）. Furthermore, among 27 cases with unilateral IJV abnormality, all the CYST occurred on the same side as the IJV lesions.展开更多
Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features,as well as its easy burying in the complex,non-stationary structural vibrations and strong bac...Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features,as well as its easy burying in the complex,non-stationary structural vibrations and strong background noises.In this paper,a method based on the flexible analytical wavelet transform(FAWT)possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings.During the route of the proposed method,the proper FAWT bases are constructed via genetic optimization algorithm(GA)based on maximizing the spectral correlated kurtosis(SCK)which is firstly presented and proved to be efficient and effective in indicating interested fault mode.Via using the customized FAWT bases for each interested fault mode,the original vibration measurements are decomposed into fine frequency subbands,and the sensitive subband which enhances the signal-to-noise ratio(SNR)is selected to exhibit the fault signature on its envelope spectrum.The proposed method is tested via simulated signals,and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace,inner-race and roller defects.The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings.展开更多
Urban electricity and heat networks(UEHN)consist of the coupling and interactions between electric power systems and district heating systems,in which the geographical and functional features of integrated energy syst...Urban electricity and heat networks(UEHN)consist of the coupling and interactions between electric power systems and district heating systems,in which the geographical and functional features of integrated energy systems are demonstrated.UEHN have been expected to provide an effective way to accommodate the intermittent and unpredictable renewable energy sources,in which the application of stochastic optimization approaches to UEHN analysis is highly desired.In this paper,we propose a chance-constrained coordinated optimization approach for UEHN considering the uncertainties in electricity loads,heat loads,and photovoltaic outputs,as well as the correlations between these uncertain sources.A solution strategy,which combines the Latin Hypercube Sampling Monte Carlo Simulation(LHSMCS)approach and a heuristic algorithm,is specifically designed to deal with the proposed chance-constrained coordinated optimization.Finally,test results on an UEHN comprised of a modified IEEE 33-bus system and a 32-node district heating system at Barry Island have verified the feasibility and effectiveness of the proposed framework.展开更多
Survival analysis is a fundamental tool in medical science for time-to-event data. However, its application to colony organisms like bees poses challenges due to their social nature. Traditional survival models may no...Survival analysis is a fundamental tool in medical science for time-to-event data. However, its application to colony organisms like bees poses challenges due to their social nature. Traditional survival models may not accurately capture the interdependence among individuals within a colony. Frailty models, accounting for shared risks within groups, offer a promising alternative. This study evaluates the performance of semi-parametric shared frailty models (gamma, inverse normal, and positive stable-in comparison to the traditional Cox model using bees’ survival data). We examined the effect of misspecification of the frailty distribution on regression and heterogeneity parameters using simulation and concluded that the heterogeneity parameter was more sensitive to misspecification of the frailty distribution and choice of initial parameters (cluster size and true heterogeneity parameter) compared to the regression parameter. From the data, parameter estimates for covariates were close for the four models but slightly higher for the Cox model. The shared gamma frailty model provided a better fit to the data in comparison with the other models. Therefore, when focusing on regression parameters, the gamma frailty model is recommended. This research underscores the importance of tailored survival methodologies for accurately analyzing time-to-event data in social organisms.展开更多
Adaptive fractional polynomial modeling of general correlated outcomes is formulated to address nonlinearity in means, variances/dispersions, and correlations. Means and variances/dispersions are modeled using general...Adaptive fractional polynomial modeling of general correlated outcomes is formulated to address nonlinearity in means, variances/dispersions, and correlations. Means and variances/dispersions are modeled using generalized linear models in fixed effects/coefficients. Correlations are modeled using random effects/coefficients. Nonlinearity is addressed using power transforms of primary (untransformed) predictors. Parameter estimation is based on extended linear mixed modeling generalizing both generalized estimating equations and linear mixed modeling. Models are evaluated using likelihood cross-validation (LCV) scores and are generated adaptively using a heuristic search controlled by LCV scores. Cases covered include linear, Poisson, logistic, exponential, and discrete regression of correlated continuous, count/rate, dichotomous, positive continuous, and discrete numeric outcomes treated as normally, Poisson, Bernoulli, exponentially, and discrete numerically distributed, respectively. Example analyses are also generated for these five cases to compare adaptive random effects/coefficients modeling of correlated outcomes to previously developed adaptive modeling based on directly specified covariance structures. Adaptive random effects/coefficients modeling substantially outperforms direct covariance modeling in the linear, exponential, and discrete regression example analyses. It generates equivalent results in the logistic regression example analyses and it is substantially outperformed in the Poisson regression case. Random effects/coefficients modeling of correlated outcomes can provide substantial improvements in model selection compared to directly specified covariance modeling. However, directly specified covariance modeling can generate competitive or substantially better results in some cases while usually requiring less computation time.展开更多
Mott insulator material,as a kind of strongly correlated electronic system with the characteristic of a drastic change in electrical conductivity,shows excellent application prospects in neuromorphological calculation...Mott insulator material,as a kind of strongly correlated electronic system with the characteristic of a drastic change in electrical conductivity,shows excellent application prospects in neuromorphological calculations and has attracted significant attention in the scientific community.Especially,computing systems based on Mott insulators can overcome the bottleneck of separated data storage and calculation in traditional artificial intelligence systems based on the von Neumann architecture,with the potential to save energy,increase operation speed,improve integration,scalability,and three-dimensionally stacked,and more suitable to neuromorphic computing than a complementary metal-oxide-semiconductor.In this review,we have reviewed Mott insulator materials,methods for driving Mott insulator transformation(pressure-,voltage-,and temperature-driven approaches),and recent relevant applications in neuromorphic calculations.The results in this review provide a path for further study of the applications in neuromorphic calculations based on Mott insulator materials and the related devices.展开更多
Recently,Lee et al.claimed the experimental discovery of room-temperature ambient-pressure super-conductivity in a Cu-doped lead-apatite(LK-99)(arXiv:2307.12008,arXiv:2307.12037).Remarkably,the claimed superconductivi...Recently,Lee et al.claimed the experimental discovery of room-temperature ambient-pressure super-conductivity in a Cu-doped lead-apatite(LK-99)(arXiv:2307.12008,arXiv:2307.12037).Remarkably,the claimed superconductivity can persist up to 400 K at ambient pressure.Despite the experimental im-plication,the electronic structure of LK-99 has not yet been studied.Here,we investigate the electronic structures of LK-99 and its parent compound using first-principles calculations,aiming to elucidate the doping effects of Cu.Our results reveal that the parent compound Pb_(10)(PO_(4))_(6)O is an insulator,while Cu doping induces an insulator-metal transition and thus volume contraction.The band structures of LK-99 around the Fermi level are featured by a half-filled flat band and a fully-occupied flat band.These two very flat bands arise from both the 2p orbitals of 1/4-occupied O atoms and the hybridization of the 3d orbitals of Cu with the 2p orbitals of its nearest-neighboring O atoms.Interestingly,we observe four van Hove singularities on these two flat bands.Furthermore,we show that the flat band structures can be tuned by including electronic correlation effects or by doping different elements.We find that among the considered doping elements(Ni,Cu,Zn,Ag,and Au),both Ni and Zn doping result in the gap opening,whereas Au exhibits doping effects more similar to Cu than Ag.Our work establishes a foundation for fu-ture studies to investigate the role of unique electronic structures of LK-99 in its claimed superconducting properties.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
Rare-earth nickelates(RENiO_(3))show widely tunable metal-to-insulator transition(MIT)properties with ignorable variations in lattice constants and small latent heat across the critical temperature(TMIT).Particularly,...Rare-earth nickelates(RENiO_(3))show widely tunable metal-to-insulator transition(MIT)properties with ignorable variations in lattice constants and small latent heat across the critical temperature(TMIT).Particularly,it is worth noting that compared with the more commonly investigated vanadium oxides,the MIT of RENiO_(3)is less abrupt but usually across a wider range of temperatures.This sheds light on their alternative applications as negative temperature coefficient resistance(NTCR)thermistors with high sensitivity compared with the current NTCR thermistors,other than their expected use as critical temperature resistance thermistors.In this work,we demonstrate the NTCR thermistor functionality for using the adjustable MIT of Nd_(x)Sm_(1-x)NiO_(3)within 200–400 K,which displays larger magnitudes of NTCR(e.g.,more than 7%/K)that is unattainable in traditional NTCR thermistor materials.The temperature dependence of resistance(R–T)shows sharp variation during the MIT of Nd_(x)Sm_(1-x)NiO_(3)with no hysteresis via decreasing the Nd content(e.g.,x≤0.8),and such a R–T tendency can be linearized by introducing an optimum parallel resistor.The sensitive range of temperature can be further extended to 210–360 K by combining a series of Nd_(x)Sm_(1-x)NiO_(3)with eight rare-earth co-occupation ratios as an array,with a high magnitude of NTCR(e.g.,7%–14%/K)covering the entire range of temperatures.展开更多
BACKGROUND Hepatocellular carcinoma(HCC)is an aggressive subtype of liver cancer and is one of the most common cancers with high mortality worldwide.Reprogrammed lipid metabolism plays crucial roles in HCC cancer cell...BACKGROUND Hepatocellular carcinoma(HCC)is an aggressive subtype of liver cancer and is one of the most common cancers with high mortality worldwide.Reprogrammed lipid metabolism plays crucial roles in HCC cancer cell survival,growth,and evolution.Emerging evidence suggests the importance of fatty acid binding proteins(FABPs)in contribution to cancer progression and metastasis;however,how these FABPs are dysregulated in cancer cells,especially in HCC,and the roles of FABPs in cancer progression have not been well defined.AIM To understand the genetic alterations and expression of FABPs and their associated cancer hallmarks and oncogenes in contributing to cancer malignancies.METHODS We used The Cancer Genome Atlas datasets of pan cancer and liver hepatocellular carcinoma(LIHC)as well as patient cohorts with other cancer types in this study.We investigated genetic alterations of FABPs in various cancer types.mRNA expression was used to determine if FABPs are abnormally expressed in tumor tissues compared to non-tumor controls and to investigate whether their expression correlates with patient clinical outcome,enriched cancer hallmarks and oncogenes previously reported for patients with HCC.We determined the protein levels of FABP5 and its correlated genes in two HCC cell lines and assessed the potential of FABP5 inhibition in treating HCC cells.RESULTS We discovered that a gene cluster including five FABP family members(FABP4,FABP5,FABP8,FABP9 and FABP12)is frequently co-amplified in cancer.Amplification,in fact,is the most common genetic alteration for FABPs,leading to overexpression of FABPs.FABP5 showed the greatest differential mRNA expression comparing tumor with non-tumor tissues.High FABP5 expression correlates well with worse patient outcomes(P<0.05).FABP5 expression highly correlates with enrichment of G2M checkpoint(r=0.33,P=1.1e-10),TP53 signaling pathway(r=0.22,P=1.7e-5)and many genes in the gene sets such as CDK1(r=0.56,P=0),CDK4(r=0.49,P=0),and TP53(r=0.22,P=1.6e-5).Furthermore,FABP5 also correlates 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
Structural change in panel data is a widespread phenomena. This paper proposes a fluctuation test to detect a structural change at an unknown date in heterogeneous panel data models with or without common correlated e...Structural change in panel data is a widespread phenomena. This paper proposes a fluctuation test to detect a structural change at an unknown date in heterogeneous panel data models with or without common correlated effects. The asymptotic properties of the fluctuation statistics in two cases are developed under the null and local alternative hypothesis. Furthermore, the consistency of the change point estimator is proven. Monte Carlo simulation shows that the fluctuation test can control the probability of type I error in most cases, and the empirical power is high in case of small and moderate sample sizes. An application of the procedure to a real data is presented.展开更多
For accurate Finite Element(FE)modeling for the structural dynamics of aeroengine casings,Parametric Modeling-based Model Updating Strategy(PM-MUS)is proposed based on efficient FE parametric modeling and model updati...For accurate Finite Element(FE)modeling for the structural dynamics of aeroengine casings,Parametric Modeling-based Model Updating Strategy(PM-MUS)is proposed based on efficient FE parametric modeling and model updating techniques regarding uncorrelated/correlated mode shapes.Casings structure is parametrically modeled by simplifying initial structural FE model and equivalently simulating mechanical characteristics.Uncorrelated modes between FE model and experiment are reasonably handled by adopting an objective function to recognize correct correlated modes pairs.The parametrized FE model is updated to effectively describe structural dynamic characteristics in respect of testing data.The model updating technology is firstly validated by the detailed FE model updating of one fixed–fixed beam structure in light of correlated/uncorrelated mode shapes and measured mode data.The PM-MUS is applied to the FE parametrized model updating of an aeroengine stator system(casings)which is constructed by the proposed parametric modeling approach.As revealed in this study,(A)the updated models by the proposed updating strategy and dynamic test data is accurate,and(B)the uncorrelated modes like close modes can be effectively handled and precisely identify the FE model mode associated the corresponding experimental mode,and(C)parametric modeling can enhance the dynamic modeling updating of complex structure in the accuracy of mode matching.The efforts of this study provide an efficient dynamic model updating strategy(PM-MUS)for aeroengine casings by parametric modeling and experimental test data regarding uncorrelated modes.展开更多
The penalized variable selection methods are often used to select the relevant covariates and estimate the unknown regression coefficients simultaneously,but these existing methods may fail to be consistent for the se...The penalized variable selection methods are often used to select the relevant covariates and estimate the unknown regression coefficients simultaneously,but these existing methods may fail to be consistent for the setting with highly correlated covariates.In this paper,the semi-standard partial covariance(SPAC)method with Lasso penalty is proposed to study the generalized linear model with highly correlated covariates,and the consistencies of the estimation and variable selection are shown in high-dimensional settings under some regularity conditions.Some simulation studies and an analysis of colon tumor dataset are carried out to show that the proposed method performs better in addressing highly correlated problem than the traditional penalized variable selection methods.展开更多
基金supported by the National Natural Science Foundation of China (Nos.60934009,60804064,and 30800248)the China Post-doctoral Science Foundation (No.20100471727)the Science and Technology Department of Zhejiang Province,China (No.2009C34016)
文摘Square-root cubature Kalman filter (SCKF) is more effective for nonlinear state estimation than an unscented Kalman filter.In this paper,we study the design of nonlinear filters based on SCKF for the system with one step noise correlation and abrupt state change.First,we give the SCKF that deals with the one step correlation between process and measurement noises,SCKF-CN in short.Second,we introduce the idea of a strong tracking filter to construct the adaptive square-root factor of the prediction error covariance with a fading factor,which makes SCKF-CN obtain outstanding tracking performance to the system with target maneuver or abrupt state change.Accordingly,the tracking performance of SCKF is greatly improved.A universal nonlinear estimator is proposed,which can not only deal with the conventional nonlinear filter problem with high dimensionality and correlated noises,but also achieve an excellent strong tracking performance towards the abrupt change of target state.Three simulation examples with a bearings-only tracking system are illustrated to verify the efficiency of the proposed algorithms.
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This research was supported by grants from Research Fund for the Doctoral Program of Higher Education of China （No. 20111107120001） and National Natural Science Foundation of China （No. 81200912）.
文摘Background Cerebral venous sinus thrombosis （CVST） is a special form of stroke with multiple causes and risk factors. However, there are still a portion of cases with unknown reasons. The aim of this study was to investigate the relationship between internal jugular vein （IJV） abnormalities and the development of CVST. Methods A total of 51 CVST patients and 30 healthy controls were enrolled. The diameter, the maximum velocity （Vmax） and the reflux time in bilateral IJVs were measured by color Doppler flow imaging （CDFI）. The paired t test was used to compare the numeric values between the bilateral IJVs. The Pearson chi-square test was used to evaluate the relationship between IJV abnormality and CVST, IJV abnormality and IJV reflux, respectively. Results Among the 51 CVST patients, 20 （39%） patients were with normal IJV and 31 （61%） patients were with abnormal IJV. The types of IJV abnormality included annulus stenosis 19 cases （61%）, hypoplasia 9 cases （29%）, thrombosis 2 cases （7%） and anomalous valve 1 case （3%）. In patients with unilateral IJV abnormality, the minimum diameter of the IJV on the lesion side was significantly smaller than that of the contralateral side （P 〈0.0001）. When compared with contralateral side, the Vmax of the lesion side with unilateral annulus stenosis was significant higher, however, it was obvious lower in patients with unilateral hypoplasia （P 〈0.05）. Furthermore, among 27 cases with unilateral IJV abnormality, all the CYST occurred on the same side as the IJV lesions.
基金co-supported by the Fundamental Research Funds for the Central Universities of China,China Postdoctoral Science Foundation(No.2018M631196)the National Natural Foundation of China(No.51705420).
文摘Multi-faults detection is a challenge for rolling bearings due to the mode mixture and coupling of multiple fault features,as well as its easy burying in the complex,non-stationary structural vibrations and strong background noises.In this paper,a method based on the flexible analytical wavelet transform(FAWT)possessing fractional scaling and translation factors is proposed to identify multiple faults occurred in different components of rolling bearings.During the route of the proposed method,the proper FAWT bases are constructed via genetic optimization algorithm(GA)based on maximizing the spectral correlated kurtosis(SCK)which is firstly presented and proved to be efficient and effective in indicating interested fault mode.Via using the customized FAWT bases for each interested fault mode,the original vibration measurements are decomposed into fine frequency subbands,and the sensitive subband which enhances the signal-to-noise ratio(SNR)is selected to exhibit the fault signature on its envelope spectrum.The proposed method is tested via simulated signals,and applied to analyze the experimental vibration measurements from the running roller bearings subjected to outrace,inner-race and roller defects.The analysis results validate the effectiveness of the proposed method in identifying multi-faults occurred in different components of rolling bearings.
基金This work was supported in part by Natural Science Foundation of Jiangsu Province,China(No.BK20171433)in part by Science and Technology Project of State Grid Jiangsu Electric Power Corporation,China(No.J2018066).
文摘Urban electricity and heat networks(UEHN)consist of the coupling and interactions between electric power systems and district heating systems,in which the geographical and functional features of integrated energy systems are demonstrated.UEHN have been expected to provide an effective way to accommodate the intermittent and unpredictable renewable energy sources,in which the application of stochastic optimization approaches to UEHN analysis is highly desired.In this paper,we propose a chance-constrained coordinated optimization approach for UEHN considering the uncertainties in electricity loads,heat loads,and photovoltaic outputs,as well as the correlations between these uncertain sources.A solution strategy,which combines the Latin Hypercube Sampling Monte Carlo Simulation(LHSMCS)approach and a heuristic algorithm,is specifically designed to deal with the proposed chance-constrained coordinated optimization.Finally,test results on an UEHN comprised of a modified IEEE 33-bus system and a 32-node district heating system at Barry Island have verified the feasibility and effectiveness of the proposed framework.
文摘Survival analysis is a fundamental tool in medical science for time-to-event data. However, its application to colony organisms like bees poses challenges due to their social nature. Traditional survival models may not accurately capture the interdependence among individuals within a colony. Frailty models, accounting for shared risks within groups, offer a promising alternative. This study evaluates the performance of semi-parametric shared frailty models (gamma, inverse normal, and positive stable-in comparison to the traditional Cox model using bees’ survival data). We examined the effect of misspecification of the frailty distribution on regression and heterogeneity parameters using simulation and concluded that the heterogeneity parameter was more sensitive to misspecification of the frailty distribution and choice of initial parameters (cluster size and true heterogeneity parameter) compared to the regression parameter. From the data, parameter estimates for covariates were close for the four models but slightly higher for the Cox model. The shared gamma frailty model provided a better fit to the data in comparison with the other models. Therefore, when focusing on regression parameters, the gamma frailty model is recommended. This research underscores the importance of tailored survival methodologies for accurately analyzing time-to-event data in social organisms.
文摘Adaptive fractional polynomial modeling of general correlated outcomes is formulated to address nonlinearity in means, variances/dispersions, and correlations. Means and variances/dispersions are modeled using generalized linear models in fixed effects/coefficients. Correlations are modeled using random effects/coefficients. Nonlinearity is addressed using power transforms of primary (untransformed) predictors. Parameter estimation is based on extended linear mixed modeling generalizing both generalized estimating equations and linear mixed modeling. Models are evaluated using likelihood cross-validation (LCV) scores and are generated adaptively using a heuristic search controlled by LCV scores. Cases covered include linear, Poisson, logistic, exponential, and discrete regression of correlated continuous, count/rate, dichotomous, positive continuous, and discrete numeric outcomes treated as normally, Poisson, Bernoulli, exponentially, and discrete numerically distributed, respectively. Example analyses are also generated for these five cases to compare adaptive random effects/coefficients modeling of correlated outcomes to previously developed adaptive modeling based on directly specified covariance structures. Adaptive random effects/coefficients modeling substantially outperforms direct covariance modeling in the linear, exponential, and discrete regression example analyses. It generates equivalent results in the logistic regression example analyses and it is substantially outperformed in the Poisson regression case. Random effects/coefficients modeling of correlated outcomes can provide substantial improvements in model selection compared to directly specified covariance modeling. However, directly specified covariance modeling can generate competitive or substantially better results in some cases while usually requiring less computation time.
基金This work was financially supported by the National Key Research&Development Plan“Nano Frontier”Key Special Project(No.2021YFA1200502)Cultivation projects of national major Research&Development project(No.92164109)+11 种基金the National Natural Science Foundation of China(Nos.61874158,62004056,and 62104058)Special project of strategic leading science and technology of Chinese Academy of Sciences(No.XDB44000000-7)Hebei Basic Research Special Key Project(No.F2021201045)Support Program for the Top Young Talents of Hebei Province(No.70280011807)Supporting Plan for 100 Excellent Innovative Talents in Colleges and Universities of Hebei Province(No.SLRC2019018)Interdisciplinary Research Program of Natural Science of Hebei University(No.DXK202101)Institute of Life Sciences and Green Development(No.521100311)Natural Science Foundation of Hebei Province(Nos.F2022201054 and F2021201022)Outstanding Young Scientific Research and Innovation Team of Hebei University(No.605020521001)Special Support Funds for National High Level Talents(No.041500120001)Advanced Talents Incubation Program of the Hebei University(Nos.521000981426,521100221071,and 521000981363)Funded by Science and Technology Project of Hebei Education Department(Nos.QN2020178 and QN2021026).
文摘Mott insulator material,as a kind of strongly correlated electronic system with the characteristic of a drastic change in electrical conductivity,shows excellent application prospects in neuromorphological calculations and has attracted significant attention in the scientific community.Especially,computing systems based on Mott insulators can overcome the bottleneck of separated data storage and calculation in traditional artificial intelligence systems based on the von Neumann architecture,with the potential to save energy,increase operation speed,improve integration,scalability,and three-dimensionally stacked,and more suitable to neuromorphic computing than a complementary metal-oxide-semiconductor.In this review,we have reviewed Mott insulator materials,methods for driving Mott insulator transformation(pressure-,voltage-,and temperature-driven approaches),and recent relevant applications in neuromorphic calculations.The results in this review provide a path for further study of the applications in neuromorphic calculations based on Mott insulator materials and the related devices.
文摘Recently,Lee et al.claimed the experimental discovery of room-temperature ambient-pressure super-conductivity in a Cu-doped lead-apatite(LK-99)(arXiv:2307.12008,arXiv:2307.12037).Remarkably,the claimed superconductivity can persist up to 400 K at ambient pressure.Despite the experimental im-plication,the electronic structure of LK-99 has not yet been studied.Here,we investigate the electronic structures of LK-99 and its parent compound using first-principles calculations,aiming to elucidate the doping effects of Cu.Our results reveal that the parent compound Pb_(10)(PO_(4))_(6)O is an insulator,while Cu doping induces an insulator-metal transition and thus volume contraction.The band structures of LK-99 around the Fermi level are featured by a half-filled flat band and a fully-occupied flat band.These two very flat bands arise from both the 2p orbitals of 1/4-occupied O atoms and the hybridization of the 3d orbitals of Cu with the 2p orbitals of its nearest-neighboring O atoms.Interestingly,we observe four van Hove singularities on these two flat bands.Furthermore,we show that the flat band structures can be tuned by including electronic correlation effects or by doping different elements.We find that among the considered doping elements(Ni,Cu,Zn,Ag,and Au),both Ni and Zn doping result in the gap opening,whereas Au exhibits doping effects more similar to Cu than Ag.Our work establishes a foundation for fu-ture studies to investigate the role of unique electronic structures of LK-99 in its claimed superconducting properties.
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.
基金the National Key Research and Development Program of China(No.2021YFA0718900)the National Natural Science Foundation of China(No.62074014)。
文摘Rare-earth nickelates(RENiO_(3))show widely tunable metal-to-insulator transition(MIT)properties with ignorable variations in lattice constants and small latent heat across the critical temperature(TMIT).Particularly,it is worth noting that compared with the more commonly investigated vanadium oxides,the MIT of RENiO_(3)is less abrupt but usually across a wider range of temperatures.This sheds light on their alternative applications as negative temperature coefficient resistance(NTCR)thermistors with high sensitivity compared with the current NTCR thermistors,other than their expected use as critical temperature resistance thermistors.In this work,we demonstrate the NTCR thermistor functionality for using the adjustable MIT of Nd_(x)Sm_(1-x)NiO_(3)within 200–400 K,which displays larger magnitudes of NTCR(e.g.,more than 7%/K)that is unattainable in traditional NTCR thermistor materials.The temperature dependence of resistance(R–T)shows sharp variation during the MIT of Nd_(x)Sm_(1-x)NiO_(3)with no hysteresis via decreasing the Nd content(e.g.,x≤0.8),and such a R–T tendency can be linearized by introducing an optimum parallel resistor.The sensitive range of temperature can be further extended to 210–360 K by combining a series of Nd_(x)Sm_(1-x)NiO_(3)with eight rare-earth co-occupation ratios as an array,with a high magnitude of NTCR(e.g.,7%–14%/K)covering the entire range of temperatures.
基金Tianjin Key Medical Discipline Construction Project,No.TJYXZDXK-034A.
文摘BACKGROUND Hepatocellular carcinoma(HCC)is an aggressive subtype of liver cancer and is one of the most common cancers with high mortality worldwide.Reprogrammed lipid metabolism plays crucial roles in HCC cancer cell survival,growth,and evolution.Emerging evidence suggests the importance of fatty acid binding proteins(FABPs)in contribution to cancer progression and metastasis;however,how these FABPs are dysregulated in cancer cells,especially in HCC,and the roles of FABPs in cancer progression have not been well defined.AIM To understand the genetic alterations and expression of FABPs and their associated cancer hallmarks and oncogenes in contributing to cancer malignancies.METHODS We used The Cancer Genome Atlas datasets of pan cancer and liver hepatocellular carcinoma(LIHC)as well as patient cohorts with other cancer types in this study.We investigated genetic alterations of FABPs in various cancer types.mRNA expression was used to determine if FABPs are abnormally expressed in tumor tissues compared to non-tumor controls and to investigate whether their expression correlates with patient clinical outcome,enriched cancer hallmarks and oncogenes previously reported for patients with HCC.We determined the protein levels of FABP5 and its correlated genes in two HCC cell lines and assessed the potential of FABP5 inhibition in treating HCC cells.RESULTS We discovered that a gene cluster including five FABP family members(FABP4,FABP5,FABP8,FABP9 and FABP12)is frequently co-amplified in cancer.Amplification,in fact,is the most common genetic alteration for FABPs,leading to overexpression of FABPs.FABP5 showed the greatest differential mRNA expression comparing tumor with non-tumor tissues.High FABP5 expression correlates well with worse patient outcomes(P<0.05).FABP5 expression highly correlates with enrichment of G2M checkpoint(r=0.33,P=1.1e-10),TP53 signaling pathway(r=0.22,P=1.7e-5)and many genes in the gene sets such as CDK1(r=0.56,P=0),CDK4(r=0.49,P=0),and TP53(r=0.22,P=1.6e-5).Furthermore,FABP5 also correlates
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 the National Natural Science Foundation of China under Grant Nos. 11801438,12161072 and 12171388the Natural Science Basic Research Plan in Shaanxi Province of China under Grant No. 2023-JC-YB-058the Innovation Capability Support Program of Shaanxi under Grant No. 2020PT-023。
文摘Structural change in panel data is a widespread phenomena. This paper proposes a fluctuation test to detect a structural change at an unknown date in heterogeneous panel data models with or without common correlated effects. The asymptotic properties of the fluctuation statistics in two cases are developed under the null and local alternative hypothesis. Furthermore, the consistency of the change point estimator is proven. Monte Carlo simulation shows that the fluctuation test can control the probability of type I error in most cases, and the empirical power is high in case of small and moderate sample sizes. An application of the procedure to a real data is presented.
基金co-supported by National Natural Science Foundation of China(Nos.51975124 and 51675179)Shanghai International Cooperation Project of One Belt and One Road of China(No.20110741700)Research Startup Fund of Fudan University(No.FDU38341)。
文摘For accurate Finite Element(FE)modeling for the structural dynamics of aeroengine casings,Parametric Modeling-based Model Updating Strategy(PM-MUS)is proposed based on efficient FE parametric modeling and model updating techniques regarding uncorrelated/correlated mode shapes.Casings structure is parametrically modeled by simplifying initial structural FE model and equivalently simulating mechanical characteristics.Uncorrelated modes between FE model and experiment are reasonably handled by adopting an objective function to recognize correct correlated modes pairs.The parametrized FE model is updated to effectively describe structural dynamic characteristics in respect of testing data.The model updating technology is firstly validated by the detailed FE model updating of one fixed–fixed beam structure in light of correlated/uncorrelated mode shapes and measured mode data.The PM-MUS is applied to the FE parametrized model updating of an aeroengine stator system(casings)which is constructed by the proposed parametric modeling approach.As revealed in this study,(A)the updated models by the proposed updating strategy and dynamic test data is accurate,and(B)the uncorrelated modes like close modes can be effectively handled and precisely identify the FE model mode associated the corresponding experimental mode,and(C)parametric modeling can enhance the dynamic modeling updating of complex structure in the accuracy of mode matching.The efforts of this study provide an efficient dynamic model updating strategy(PM-MUS)for aeroengine casings by parametric modeling and experimental test data regarding uncorrelated modes.
基金Supported by the National Natural Science Foundation of China(Grant Nos.12001277,12271046 and 12131006)。
文摘The penalized variable selection methods are often used to select the relevant covariates and estimate the unknown regression coefficients simultaneously,but these existing methods may fail to be consistent for the setting with highly correlated covariates.In this paper,the semi-standard partial covariance(SPAC)method with Lasso penalty is proposed to study the generalized linear model with highly correlated covariates,and the consistencies of the estimation and variable selection are shown in high-dimensional settings under some regularity conditions.Some simulation studies and an analysis of colon tumor dataset are carried out to show that the proposed method performs better in addressing highly correlated problem than the traditional penalized variable selection methods.
