In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken a...In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.展开更多
Estimation of random errors, which are due to shot noise of photomultiplier tube(PMT) or avalanche photodiode(APD) detectors, is very necessary in lidar observation. Due to the Poisson distribution of incident electro...Estimation of random errors, which are due to shot noise of photomultiplier tube(PMT) or avalanche photodiode(APD) detectors, is very necessary in lidar observation. Due to the Poisson distribution of incident electrons, there still exists a proportional relationship between standard deviation and square root of its mean value. Based on this relationship,noise scale factor(NSF) is introduced into the estimation, which only needs a single data sample. This method overcomes the distractions of atmospheric fluctuations during calculation of random errors. The results show that this method is feasible and reliable.展开更多
The effects of statistically dependent random errors on the sidelobe are analyzed for the linear array. It is shown that the random errors cause a rise in the sidelobe level. The simple formulas can also be obtained f...The effects of statistically dependent random errors on the sidelobe are analyzed for the linear array. It is shown that the random errors cause a rise in the sidelobe level. The simple formulas can also be obtained for the case of independent random errors.展开更多
Chaos theory has taught us that a system which has both nonlinearity and random input will most likely produce irregular data. If random errors are irregular data, then random error process will raise nonlinearity (Ka...Chaos theory has taught us that a system which has both nonlinearity and random input will most likely produce irregular data. If random errors are irregular data, then random error process will raise nonlinearity (Kantz and Schreiber (1997)). Tsai (1986) introduced a composite test for autocorrelation and heteroscedasticity in linear models with AR(1) errors. Liu (2003) introduced a composite test for correlation and heteroscedasticity in nonlinear models with DBL(p, 0, 1) errors. Therefore, the important problems in regres- sion model are detections of bilinearity, correlation and heteroscedasticity. In this article, the authors discuss more general case of nonlinear models with DBL(p, q, 1) random errors by score test. Several statistics for the test of bilinearity, correlation, and heteroscedas- ticity are obtained, and expressed in simple matrix formulas. The results of regression models with linear errors are extended to those with bilinear errors. The simulation study is carried out to investigate the powers of the test statistics. All results of this article extend and develop results of Tsai (1986), Wei, et al (1995), and Liu, et al (2003).展开更多
BACKGROUND In observational studies,dietary intakes are associated with gastroesophageal re-flux disease(GERD).AIM To conduct a two-sample mendelian randomization(MR)analysis to determine whether those associations ar...BACKGROUND In observational studies,dietary intakes are associated with gastroesophageal re-flux disease(GERD).AIM To conduct a two-sample mendelian randomization(MR)analysis to determine whether those associations are causal.METHODS To explore the relationship between dietary intake and the risk of GERD,we extracted appropriate single nucleotide polymorphisms from genome-wide asso-ciation study data on 24 dietary intakes.Three methods were adopted for data analysis:Inverse variance weighting,weighted median methods,and MR-Egger's method.The odds ratio(OR)and 95%confidence interval(CI)were used to eva-luate the causal association between dietary intake and GERD.RESULTS Our univariate Mendelian randomization(UVMR)results showed significant evidence that pork intake(OR,2.83;95%CI:1.76-4.55;P=1.84×10–5),beer intake(OR,2.70,95%CI:2.00-3.64;P=6.54×10–11),non-oily fish intake(OR,2.41;95%CI:1.49-3.91;P=3.59×10–4)have a protective effect on GERD.In addition,dried fruit intake(OR,0.37;95%CI:0.27-0.50;6.27×10–11),red wine intake(OR,0.34;95%CI:0.25-0.47;P=1.90×10-11),cheese intake(OR,0.46;95%CI:0.39-0.55;P=3.73×10-19),bread intake(OR,0.72;95%CI:0.56-0.92;P=0.0009)and cereal intake(OR,0.45;95%CI:0.36-0.57;P=2.07×10-11)were negatively associated with the risk of GERD.There was a suggestive asso-ciation for genetically predicted coffee intake(OR per one SD increase,1.22,95%CI:1.03-1.44;P=0.019).Multi-variate Mendelian randomization further confirmed that dried fruit intake,red wine intake,cheese intake,and cereal intake directly affected GERD.In contrast,the impact of pork intake,beer intake,non-oily fish intake,and bread intake on GERD was partly driven by the common risk factors for GERD.However,after adjusting for all four elements,there was no longer a suggestive association between coffee intake and GERD.CONCLUSION This study provides MR evidence to support the causal relationship between a broad range of dietary intake and GERD,providing new insights for the treatment and prevention of GERD.展开更多
Background Educational inequalities in suicide have become increasingly prominent over the past decade.Elucidating modifiable risk factors that serve as intermediaries in the impact of low educational attainment on su...Background Educational inequalities in suicide have become increasingly prominent over the past decade.Elucidating modifiable risk factors that serve as intermediaries in the impact of low educational attainment on suicide has the potential to reduce health disparities.Aims To examine the risk factors that mediate the relationship between educational attainment and suicide attempts and quantify their contributions to the mediation effect.Methods We conducted a two-sample Mendelian randomisation(MR)analysis to estimate the causal effect of educational attainment on suicide attempts,utilising genome-wide association study summary statistics from the Integrative Psychiatric Research(iPSYCH;6024 cases and 44240 controls)and FinnGen(8978 cases and 368299 controls).We systematically evaluated 42 putative mediators within the causal pathway connecting reduced educational attainment to suicide attempts and employed two-step and multivariable MR to quantify the proportion of the mediated effect.Results In the combined analysis of iPSYCH and FinnGen,each standard deviation(SD)decrease in genetically predicted educational attainment(equating to 3.4 years of education)was associated with a 105%higher risk of suicide attempts(odds ratio(OR):2.05;95%confidence interval(Cl):1.81 to 2.31).0f the 42 risk factors analysed,the two-step MR identified five factors that mediated the association between educational attainment and suicide attempts.The respective proportions of mediation were 47%(95%Cl:29%to 66%)for smoking behaviour,36%(95%Cl:0%to 84%)for chronic pain,49%(95%Cl:36%to 61%)for depression,35%(95%Cl:12%to 59%)for anxiety and 26%(95%Cl:18%to 34%)for insomnia.Multivariable MR implicated these five mediators collectively,accounting for 68%(95%Cl:40%to 96%)of the total effect.Conclusions This study identified smoking,chronic pain and mental disorders as primary intervention targets for attenuating suicide risk attributable to lower educational levels in the European population.展开更多
In the practical environment,it is very common for the simultaneous occurrence of base excitation and crosswind.Scavenging the combined energy of vibration and wind with a single energy harvesting structure is fascina...In the practical environment,it is very common for the simultaneous occurrence of base excitation and crosswind.Scavenging the combined energy of vibration and wind with a single energy harvesting structure is fascinating.For this purpose,the effects of the wind speed and random excitation level are investigated with the stochastic averaging method(SAM)based on the energy envelope.The results of the analytical prediction are verified with the Monte-Carlo method(MCM).The numerical simulation shows that the introduction of wind can reduce the critical excitation level for triggering an inter-well jump and make a bi-stable energy harvester(BEH)realize the performance enhancement for a weak base excitation.However,as the strength of the wind increases to a particular level,the influence of the random base excitation on the dynamic responses is weakened,and the system exhibits a periodic galloping response.A comparison between a BEH and a linear energy harvester(LEH)indicates that the BEH demonstrates inferior performance for high-speed wind.Relevant experiments are conducted to investigate the validity of the theoretical prediction and numerical simulation.The experimental findings also show that strong random excitation is favorable for the BEH in the range of low wind speeds.However,as the speed of the incoming wind is up to a particular level,the disadvantage of the BEH becomes clear and evident.展开更多
This paper investigates the low earth orbit(LEO)satellite-enabled coded compressed sensing(CCS)unsourced random access(URA)in orthogonal frequency division multiple access(OFDMA)framework,where a massive uniform plana...This paper investigates the low earth orbit(LEO)satellite-enabled coded compressed sensing(CCS)unsourced random access(URA)in orthogonal frequency division multiple access(OFDMA)framework,where a massive uniform planar array(UPA)is equipped on the satellite.In LEO satellite communications,unavoidable timing and frequency offsets cause phase shifts in the transmitted signals,substantially diminishing the decoding performance of current terrestrial CCS URA receiver.To cope with this issue,we expand the inner codebook with predefined timing and frequency offsets and formulate the inner decoding as a tractable compressed sensing(CS)problem.Additionally,we leverage the inherent sparsity of the UPA-equipped LEO satellite angular domain channels,thereby enabling the outer decoder to support more active devices.Furthermore,the outputs of the outer decoder are used to reduce the search space of the inner decoder,which cuts down the computational complexity and accelerates the convergence of the inner decoding.Simulation results verify the effectiveness of the proposed scheme.展开更多
Reducing the process variation is a significant concern for resistive random access memory(RRAM).Due to its ultrahigh integration density,RRAM arrays are prone to lithographic variation during the lithography process,...Reducing the process variation is a significant concern for resistive random access memory(RRAM).Due to its ultrahigh integration density,RRAM arrays are prone to lithographic variation during the lithography process,introducing electrical variation among different RRAM devices.In this work,an optical physical verification methodology for the RRAM array is developed,and the effects of different layout parameters on important electrical characteristics are systematically investigated.The results indicate that the RRAM devices can be categorized into three clusters according to their locations and lithography environments.The read resistance is more sensitive to the locations in the array(~30%)than SET/RESET voltage(<10%).The increase in the RRAM device length and the application of the optical proximity correction technique can help to reduce the variation to less than 10%,whereas it reduces RRAM read resistance by 4×,resulting in a higher power and area consumption.As such,we provide design guidelines to minimize the electrical variation of RRAM arrays due to the lithography process.展开更多
AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was...AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was cross-sectional.Totally 3343 participants were included in the study.The initial examination involved assessing the uncorrected distance visual acuity(UDVA)and visual acuity(VA)while using a+2.00 D lens.The inclusion criteria for a subsequent comprehensive cycloplegic eye examination,performed by an optometrist,were as follows:a UDVA<0.6 decimal(0.20 logMAR)and/or a VA with+2.00 D≥0.8 decimal(0.96 logMAR).RESULTS:The sample had a mean age of 10.92±2.13y(range 4 to 17y),and 51.3%of the children were female(n=1715).The majority of the children(89.7%)fell within the age range of 8 to 14y.Among the ethnic groups,the highest representation was from the Luhya group(60.6%)followed by Luo(20.4%).Mean logMAR UDVA choosing the best eye for each student was 0.29±0.17(range 1.70 to 0.22).Out of the total,246 participants(7.4%)had a full eye examination.The estimated prevalence of myopia(defined as spherical equivalent≤-0.5 D)was found to be 1.45%of the total sample.While around 0.18%of the total sample had hyperopia value exceeding+1.75 D.Refractive astigmatism(cil<-0.75 D)was found in 0.21%(7/3343)of the children.The VI prevalence was 1.26%of the total sample.Among our cases of VI,76.2%could be attributed to uncorrected refractive error.Amblyopia was detected in 0.66%(22/3343)of the screened children.There was no statistically significant correlation observed between age or gender and refractive values.CONCLUSION:The primary cause of VI is determined to be uncorrected refractive errors,with myopia being the most prevalent refractive error observed.These findings underscore the significance of early identification and correction of refractive errors in school-aged children as a means to alleviate the impact of VI.展开更多
The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness...The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments.To address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed analysis.This analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.展开更多
In the context of global mean square error concerning the number of random variables in the representation,the Karhunen–Loève(KL)expansion is the optimal series expansion method for random field discretization.T...In the context of global mean square error concerning the number of random variables in the representation,the Karhunen–Loève(KL)expansion is the optimal series expansion method for random field discretization.The computational efficiency and accuracy of the KL expansion are contingent upon the accurate resolution of the Fredholm integral eigenvalue problem(IEVP).The paper proposes an interpolation method based on different interpolation basis functions such as moving least squares(MLS),least squares(LS),and finite element method(FEM)to solve the IEVP.Compared with the Galerkin method based on finite element or Legendre polynomials,the main advantage of the interpolation method is that,in the calculation of eigenvalues and eigenfunctions in one-dimensional random fields,the integral matrix containing covariance function only requires a single integral,which is less than a two-folded integral by the Galerkin method.The effectiveness and computational efficiency of the proposed interpolation method are verified through various one-dimensional examples.Furthermore,based on theKL expansion and polynomial chaos expansion,the stochastic analysis of two-dimensional regular and irregular domains is conducted,and the basis function of the extended finite element method(XFEM)is introduced as the interpolation basis function in two-dimensional irregular domains to solve the IEVP.展开更多
Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods ...Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods We analyzed two-sample of Mendelian randomization(2SMR)using genetic variant depression(n=113,154)and MDD(n=208,811)from Genome-Wide Association Studies(GWAS).Separate calculations were performed with modifiable risk factors from MR-Base for 1,001 genomes.The MR analysis was performed by screening drug targets with MDD in the DrugBank database to explore the therapeutic targets for MDD.Inverse variance weighted(IVW),fixed-effect inverse variance weighted(FE-IVW),MR-Egger,weighted median,and weighted mode were used for complementary calculation.Results The potential causal relationship between modifiable risk factors and depression contained 459 results for depression and 424 for MDD.Also,the associations between drug targets and MDD showed that SLC6A4,GRIN2A,GRIN2C,SCN10A,and IL1B expression are associated with an increased risk of depression.In contrast,ADRB1,CHRNA3,HTR3A,GSTP1,and GABRG2 genes are candidate protective factors against depression.Conclusion This study identified the risk factors causally associated with depression and MDD,and estimated 10 drug targets with significant impact on MDD,providing essential information for formulating strategies to prevent and treat depression.展开更多
Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function,leading to ...Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function,leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and accuracy.In this case,by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory,a random forest(RF)model is presented to enhance the computing efficiency of reliability degree;moreover,by embedding the RF model into multilevel optimization model,an efficient RF-assisted fatigue reliability-based design optimization framework is developed.Regarding the low-cycle fatigue reliability-based design optimization of aeroengine turbine disc as a case,the effectiveness of the presented framework is validated.The reliabilitybased design optimization results exhibit that the proposed framework holds high computing accuracy and computing efficiency.The current efforts shed a light on the theory/method development of reliability-based design optimization of complex engineering structures.展开更多
Insertional mutation,phenotypic evaluation,and mutated gene cloning are widely used to clone genes from scratch.Exogenous genes can be integrated into the genome during non-homologous end joining(NHEJ)of the double-st...Insertional mutation,phenotypic evaluation,and mutated gene cloning are widely used to clone genes from scratch.Exogenous genes can be integrated into the genome during non-homologous end joining(NHEJ)of the double-strand breaks of DNA,causing insertional mutation.The random insertional mutant library constructed using this method has become a method of forward genetics for gene cloning.However,the establishment of a random insertional mutant library requires a high transformation efficiency of exogenous genes.Many microalgal species show a low transformation efficiency,making constructing random insertional mutant libraries difficult.In this study,we established a highly efficient transformation method for constructing a random insertional mutant library of Nannochloropsis oceanica,and tentatively tried to isolate its genes to prove the feasibility of the method.A gene that may control the growth rate and cell size was identified.This method will facilitate the genetic studies of N.oceanica,which should also be a reference for other microalgal species.展开更多
Mental disorders seriously affect people’s health and social stability.This Mendelian randomization(MR)study was designed to investigate the causal relationship between circulating vitamin C(VC)or 25-hydroxyvitamin D...Mental disorders seriously affect people’s health and social stability.This Mendelian randomization(MR)study was designed to investigate the causal relationship between circulating vitamin C(VC)or 25-hydroxyvitamin D(25(OH)D)levels and mental disorders.The data used for the MR analysis were derived from the summary genome-wide association studies(GWAS)database for VC and 25(OH)D and from the Finn Gen consortium for fourteen mental disorders.Based on the inverse variance weighted(IVW)method,we found a potential causal association between circulating VC and anxiety disorders(IVW:OR=1.139,95%CI:1.023-1.269,P=0.018).However,no causal association was found between VC or 25(OH)D and other mental disorders(P>0.05).In the reverse MR analysis,individuals with Alzheimer’s disease was causally associated with higher concentrations of circulating VC(P=0.012),while individuals with anxiety disorders had a negative association between the concentrations of 25(OH)D(P=0.012).However,the current evidence does not support a causal relationship between VC or 25(OH)D and other mental disorders.In addition,there was no causal association between circulating VC and 25(OH)D(P>0.05).Future studies are needed to confirm these findings and to elucidate the mechanisms of potential causality.展开更多
The article introduces a finite element procedure using the bilinear quadrilateral element or four-node rectangular element(namely Q4 element) based on a refined first-order shear deformation theory(rFSDT) and Monte C...The article introduces a finite element procedure using the bilinear quadrilateral element or four-node rectangular element(namely Q4 element) based on a refined first-order shear deformation theory(rFSDT) and Monte Carlo simulation(MCS), so-called refined stochastic finite element method to investigate the random vibration of functionally graded material(FGM) plates subjected to the moving load.The advantage of the proposed method is to use r-FSDT to improve the accuracy of classical FSDT, satisfy the stress-free condition at the plate boundaries, and combine with MCS to analyze the vibration of the FGM plate when the parameter inputs are random quantities following a normal distribution. The obtained results show that the distribution characteristics of the vibration response of the FGM plate depend on the standard deviation of the input parameters and the velocity of the moving load.Furthermore, the numerical results in this study are expected to contribute to improving the understanding of FGM plates subjected to moving loads with uncertain input parameters.展开更多
BACKGROUND While the impact of depression on cognition is well-documented,the relationship between feelings and cognition has received limited attention.AIM To explore the potential association between feelings and co...BACKGROUND While the impact of depression on cognition is well-documented,the relationship between feelings and cognition has received limited attention.AIM To explore the potential association between feelings and cognition with a twosample Mendelian randomization(MR)analysis.METHODS Our analysis utilized genome-wide association data on various feelings(fed-up feelings,n=453071;worrier/anxious feelings,n=450765;guilty feelings,n=45-0704;nervous feelings,n=450700;sensitivity/hurt feelings,n=449419;miserableness,n=454982;loneliness/isolation,n=455364;happiness,n=152348)in the European population and their impact on cognitive functions(intelligence,n=269867).Conducting a univariable MR(UVMR)analysis to assess the relationship between feelings and cognition.In this analysis,we applied the inverse variance weighting(IVW),weighted median,and MR Egger methods.Additionally,we performed sensitivity analysis(leave-one-out analysis),assessed heterogeneity(using MR-PRESSO and Cochran’s Q test),and conducted multiple validity test(employing MR-Egger regression).Subsequently,a multivariable MR(MVMR)analysis was employed to examine the impact of feelings on cognition.IVW served as the primary method in the multivariable analysis,complemented by median-based and MR-Egger methods.RESULTS In this study,UVMR indicated that sensitivity/hurt feelings may have a negative causal effect on cognition(OR=0.63,95%CI:0.43-0.92,P=0.017).After adjustment of other feelings using MVMR,a direct adverse causal effect on cognition was observed(OR_(MVMR)=0.39,95%CI:0.17-0.90,P_(MVMR)=0.027).While a potential increased risk of cognitive decline was observed for fed-up feelings in the UVMR analysis(ORUVMR=0.64,95%CI:0.42-0.97,PUVMR=0.037),this effect disappeared after adjusting for other feelings(OR_(MVMR)=1.42,95%CI:0.43-4.74,P_(MVMR)=0.569).These findings were generally consistent across MV-IVW,median-based,and MR-Egger analyses.MR-Egger regression revealed pleiotropy in the impact of worrier/anxious feelings on cognition,presenting a challenge in identifying the effect.Notably,this study did not demonstrate any significant impact of guilty feelings,nervous feelings,miserableness,or loneliness/isolation on cognition.Due to a limited number of instrumental variables for happiness,this study was unable to analyze the relationship between happiness and cognition.CONCLUSION This MR study finds that sensitivity/hurt feelings are associated with cognitive decline,while the link between worrier/anxious feelings and cognition remains inconclusive.Insufficient evidence supports direct associations between happiness,guilty feelings,nervous feelings,miserableness,loneliness/isolation,and cognition.展开更多
Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture model.Although the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial ...Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture model.Although the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial information and is sensitive to the segmentation parameter.In this study,we first present an efficient algorithm that incorporates spatial information into the Gaussian mixture model(GMM)without parameter estimation.The proposed model highlights the residual region with considerable information and constructs color saliency.Second,we incorporate the content-based color saliency as spatial information in the Gaussian mixture model.The segmentation is performed by clustering each pixel into an appropriate component according to the expectation maximization and maximum criteria.Finally,the random color histogram assigns a unique color to each cluster and creates an attractive color by default for segmentation.A random color histogram serves as an effective tool for data visualization and is instrumental in the creation of generative art,facilitating both analytical and aesthetic objectives.For experiments,we have used the Berkeley segmentation dataset BSDS-500 and Microsoft Research in Cambridge dataset.In the study,the proposed model showcases notable advancements in unsupervised image segmentation,with probabilistic rand index(PRI)values reaching 0.80,BDE scores as low as 12.25 and 12.02,compactness variations at 0.59 and 0.7,and variation of information(VI)reduced to 2.0 and 1.49 for the BSDS-500 and MSRC datasets,respectively,outperforming current leading-edge methods and yielding more precise segmentations.展开更多
In the realm of large-scale machine learning,it is crucial to explore methods for reducing computational complexity and memory demands while maintaining generalization performance.Additionally,since the collected data...In the realm of large-scale machine learning,it is crucial to explore methods for reducing computational complexity and memory demands while maintaining generalization performance.Additionally,since the collected data may contain some sensitive information,it is also of great significance to study privacy-preserving machine learning algorithms.This paper focuses on the performance of the differentially private stochastic gradient descent(SGD)algorithm based on random features.To begin,the algorithm maps the original data into a lowdimensional space,thereby avoiding the traditional kernel method for large-scale data storage requirement.Subsequently,the algorithm iteratively optimizes parameters using the stochastic gradient descent approach.Lastly,the output perturbation mechanism is employed to introduce random noise,ensuring algorithmic privacy.We prove that the proposed algorithm satisfies the differential privacy while achieving fast convergence rates under some mild conditions.展开更多
基金This work is funded by the National Natural Science Foundation of China(Grant Nos.42377164 and 52079062)the National Science Fund for Distinguished Young Scholars of China(Grant No.52222905).
文摘In the existing landslide susceptibility prediction(LSP)models,the influences of random errors in landslide conditioning factors on LSP are not considered,instead the original conditioning factors are directly taken as the model inputs,which brings uncertainties to LSP results.This study aims to reveal the influence rules of the different proportional random errors in conditioning factors on the LSP un-certainties,and further explore a method which can effectively reduce the random errors in conditioning factors.The original conditioning factors are firstly used to construct original factors-based LSP models,and then different random errors of 5%,10%,15% and 20%are added to these original factors for con-structing relevant errors-based LSP models.Secondly,low-pass filter-based LSP models are constructed by eliminating the random errors using low-pass filter method.Thirdly,the Ruijin County of China with 370 landslides and 16 conditioning factors are used as study case.Three typical machine learning models,i.e.multilayer perceptron(MLP),support vector machine(SVM)and random forest(RF),are selected as LSP models.Finally,the LSP uncertainties are discussed and results show that:(1)The low-pass filter can effectively reduce the random errors in conditioning factors to decrease the LSP uncertainties.(2)With the proportions of random errors increasing from 5%to 20%,the LSP uncertainty increases continuously.(3)The original factors-based models are feasible for LSP in the absence of more accurate conditioning factors.(4)The influence degrees of two uncertainty issues,machine learning models and different proportions of random errors,on the LSP modeling are large and basically the same.(5)The Shapley values effectively explain the internal mechanism of machine learning model predicting landslide sus-ceptibility.In conclusion,greater proportion of random errors in conditioning factors results in higher LSP uncertainty,and low-pass filter can effectively reduce these random errors.
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences(Grant No.XDB05040300)the National Natural Science Foundation of China(Grant No.41205119)
文摘Estimation of random errors, which are due to shot noise of photomultiplier tube(PMT) or avalanche photodiode(APD) detectors, is very necessary in lidar observation. Due to the Poisson distribution of incident electrons, there still exists a proportional relationship between standard deviation and square root of its mean value. Based on this relationship,noise scale factor(NSF) is introduced into the estimation, which only needs a single data sample. This method overcomes the distractions of atmospheric fluctuations during calculation of random errors. The results show that this method is feasible and reliable.
文摘The effects of statistically dependent random errors on the sidelobe are analyzed for the linear array. It is shown that the random errors cause a rise in the sidelobe level. The simple formulas can also be obtained for the case of independent random errors.
文摘Chaos theory has taught us that a system which has both nonlinearity and random input will most likely produce irregular data. If random errors are irregular data, then random error process will raise nonlinearity (Kantz and Schreiber (1997)). Tsai (1986) introduced a composite test for autocorrelation and heteroscedasticity in linear models with AR(1) errors. Liu (2003) introduced a composite test for correlation and heteroscedasticity in nonlinear models with DBL(p, 0, 1) errors. Therefore, the important problems in regres- sion model are detections of bilinearity, correlation and heteroscedasticity. In this article, the authors discuss more general case of nonlinear models with DBL(p, q, 1) random errors by score test. Several statistics for the test of bilinearity, correlation, and heteroscedas- ticity are obtained, and expressed in simple matrix formulas. The results of regression models with linear errors are extended to those with bilinear errors. The simulation study is carried out to investigate the powers of the test statistics. All results of this article extend and develop results of Tsai (1986), Wei, et al (1995), and Liu, et al (2003).
文摘BACKGROUND In observational studies,dietary intakes are associated with gastroesophageal re-flux disease(GERD).AIM To conduct a two-sample mendelian randomization(MR)analysis to determine whether those associations are causal.METHODS To explore the relationship between dietary intake and the risk of GERD,we extracted appropriate single nucleotide polymorphisms from genome-wide asso-ciation study data on 24 dietary intakes.Three methods were adopted for data analysis:Inverse variance weighting,weighted median methods,and MR-Egger's method.The odds ratio(OR)and 95%confidence interval(CI)were used to eva-luate the causal association between dietary intake and GERD.RESULTS Our univariate Mendelian randomization(UVMR)results showed significant evidence that pork intake(OR,2.83;95%CI:1.76-4.55;P=1.84×10–5),beer intake(OR,2.70,95%CI:2.00-3.64;P=6.54×10–11),non-oily fish intake(OR,2.41;95%CI:1.49-3.91;P=3.59×10–4)have a protective effect on GERD.In addition,dried fruit intake(OR,0.37;95%CI:0.27-0.50;6.27×10–11),red wine intake(OR,0.34;95%CI:0.25-0.47;P=1.90×10-11),cheese intake(OR,0.46;95%CI:0.39-0.55;P=3.73×10-19),bread intake(OR,0.72;95%CI:0.56-0.92;P=0.0009)and cereal intake(OR,0.45;95%CI:0.36-0.57;P=2.07×10-11)were negatively associated with the risk of GERD.There was a suggestive asso-ciation for genetically predicted coffee intake(OR per one SD increase,1.22,95%CI:1.03-1.44;P=0.019).Multi-variate Mendelian randomization further confirmed that dried fruit intake,red wine intake,cheese intake,and cereal intake directly affected GERD.In contrast,the impact of pork intake,beer intake,non-oily fish intake,and bread intake on GERD was partly driven by the common risk factors for GERD.However,after adjusting for all four elements,there was no longer a suggestive association between coffee intake and GERD.CONCLUSION This study provides MR evidence to support the causal relationship between a broad range of dietary intake and GERD,providing new insights for the treatment and prevention of GERD.
基金the Key Discipline of Zhejang Province in Public Health and Preventative Medicine(First Class,Category A)at the Hangzhou Medical College,China.
文摘Background Educational inequalities in suicide have become increasingly prominent over the past decade.Elucidating modifiable risk factors that serve as intermediaries in the impact of low educational attainment on suicide has the potential to reduce health disparities.Aims To examine the risk factors that mediate the relationship between educational attainment and suicide attempts and quantify their contributions to the mediation effect.Methods We conducted a two-sample Mendelian randomisation(MR)analysis to estimate the causal effect of educational attainment on suicide attempts,utilising genome-wide association study summary statistics from the Integrative Psychiatric Research(iPSYCH;6024 cases and 44240 controls)and FinnGen(8978 cases and 368299 controls).We systematically evaluated 42 putative mediators within the causal pathway connecting reduced educational attainment to suicide attempts and employed two-step and multivariable MR to quantify the proportion of the mediated effect.Results In the combined analysis of iPSYCH and FinnGen,each standard deviation(SD)decrease in genetically predicted educational attainment(equating to 3.4 years of education)was associated with a 105%higher risk of suicide attempts(odds ratio(OR):2.05;95%confidence interval(Cl):1.81 to 2.31).0f the 42 risk factors analysed,the two-step MR identified five factors that mediated the association between educational attainment and suicide attempts.The respective proportions of mediation were 47%(95%Cl:29%to 66%)for smoking behaviour,36%(95%Cl:0%to 84%)for chronic pain,49%(95%Cl:36%to 61%)for depression,35%(95%Cl:12%to 59%)for anxiety and 26%(95%Cl:18%to 34%)for insomnia.Multivariable MR implicated these five mediators collectively,accounting for 68%(95%Cl:40%to 96%)of the total effect.Conclusions This study identified smoking,chronic pain and mental disorders as primary intervention targets for attenuating suicide risk attributable to lower educational levels in the European population.
基金Project supported by the National Natural Science Foundation of China(Nos.12272355,1202520411902294)+1 种基金the Opening Foundation of Shanxi Provincial Key Laboratory for Advanced Manufacturing Technology of China(No.XJZZ202304)the Shanxi Provincial Graduate Innovation Project of China(No.2023KY629)。
文摘In the practical environment,it is very common for the simultaneous occurrence of base excitation and crosswind.Scavenging the combined energy of vibration and wind with a single energy harvesting structure is fascinating.For this purpose,the effects of the wind speed and random excitation level are investigated with the stochastic averaging method(SAM)based on the energy envelope.The results of the analytical prediction are verified with the Monte-Carlo method(MCM).The numerical simulation shows that the introduction of wind can reduce the critical excitation level for triggering an inter-well jump and make a bi-stable energy harvester(BEH)realize the performance enhancement for a weak base excitation.However,as the strength of the wind increases to a particular level,the influence of the random base excitation on the dynamic responses is weakened,and the system exhibits a periodic galloping response.A comparison between a BEH and a linear energy harvester(LEH)indicates that the BEH demonstrates inferior performance for high-speed wind.Relevant experiments are conducted to investigate the validity of the theoretical prediction and numerical simulation.The experimental findings also show that strong random excitation is favorable for the BEH in the range of low wind speeds.However,as the speed of the incoming wind is up to a particular level,the disadvantage of the BEH becomes clear and evident.
基金supported by the National Key R&D Program of China under Grant 2023YFB2904703the National Natural Science Foundation of China under Grant 62341110,62371122 and 62322104+1 种基金the Jiangsu Province Basic Research Project under Grant BK20192002the Fundamental Research Funds for the Central Universities under Grant 2242022k30005 and 2242023K5003。
文摘This paper investigates the low earth orbit(LEO)satellite-enabled coded compressed sensing(CCS)unsourced random access(URA)in orthogonal frequency division multiple access(OFDMA)framework,where a massive uniform planar array(UPA)is equipped on the satellite.In LEO satellite communications,unavoidable timing and frequency offsets cause phase shifts in the transmitted signals,substantially diminishing the decoding performance of current terrestrial CCS URA receiver.To cope with this issue,we expand the inner codebook with predefined timing and frequency offsets and formulate the inner decoding as a tractable compressed sensing(CS)problem.Additionally,we leverage the inherent sparsity of the UPA-equipped LEO satellite angular domain channels,thereby enabling the outer decoder to support more active devices.Furthermore,the outputs of the outer decoder are used to reduce the search space of the inner decoder,which cuts down the computational complexity and accelerates the convergence of the inner decoding.Simulation results verify the effectiveness of the proposed scheme.
基金supported in part by the Open Fund of State Key Laboratory of Integrated Chips and Systems,Fudan Universityin part by the National Science Foundation of China under Grant No.62304133 and No.62350610271.
文摘Reducing the process variation is a significant concern for resistive random access memory(RRAM).Due to its ultrahigh integration density,RRAM arrays are prone to lithographic variation during the lithography process,introducing electrical variation among different RRAM devices.In this work,an optical physical verification methodology for the RRAM array is developed,and the effects of different layout parameters on important electrical characteristics are systematically investigated.The results indicate that the RRAM devices can be categorized into three clusters according to their locations and lithography environments.The read resistance is more sensitive to the locations in the array(~30%)than SET/RESET voltage(<10%).The increase in the RRAM device length and the application of the optical proximity correction technique can help to reduce the variation to less than 10%,whereas it reduces RRAM read resistance by 4×,resulting in a higher power and area consumption.As such,we provide design guidelines to minimize the electrical variation of RRAM arrays due to the lithography process.
文摘AIM:To investigate the prevalence of visual impairment(VI)and provide an estimation of uncorrected refractive errors in school-aged children,conducted by optometry students as a community service.METHODS:The study was cross-sectional.Totally 3343 participants were included in the study.The initial examination involved assessing the uncorrected distance visual acuity(UDVA)and visual acuity(VA)while using a+2.00 D lens.The inclusion criteria for a subsequent comprehensive cycloplegic eye examination,performed by an optometrist,were as follows:a UDVA<0.6 decimal(0.20 logMAR)and/or a VA with+2.00 D≥0.8 decimal(0.96 logMAR).RESULTS:The sample had a mean age of 10.92±2.13y(range 4 to 17y),and 51.3%of the children were female(n=1715).The majority of the children(89.7%)fell within the age range of 8 to 14y.Among the ethnic groups,the highest representation was from the Luhya group(60.6%)followed by Luo(20.4%).Mean logMAR UDVA choosing the best eye for each student was 0.29±0.17(range 1.70 to 0.22).Out of the total,246 participants(7.4%)had a full eye examination.The estimated prevalence of myopia(defined as spherical equivalent≤-0.5 D)was found to be 1.45%of the total sample.While around 0.18%of the total sample had hyperopia value exceeding+1.75 D.Refractive astigmatism(cil<-0.75 D)was found in 0.21%(7/3343)of the children.The VI prevalence was 1.26%of the total sample.Among our cases of VI,76.2%could be attributed to uncorrected refractive error.Amblyopia was detected in 0.66%(22/3343)of the screened children.There was no statistically significant correlation observed between age or gender and refractive values.CONCLUSION:The primary cause of VI is determined to be uncorrected refractive errors,with myopia being the most prevalent refractive error observed.These findings underscore the significance of early identification and correction of refractive errors in school-aged children as a means to alleviate the impact of VI.
文摘The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments.To address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed analysis.This analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.
基金The authors gratefully acknowledge the support provided by the Postgraduate Research&Practice Program of Jiangsu Province(Grant No.KYCX18_0526)the Fundamental Research Funds for the Central Universities(Grant No.2018B682X14)Guangdong Basic and Applied Basic Research Foundation(No.2021A1515110807).
文摘In the context of global mean square error concerning the number of random variables in the representation,the Karhunen–Loève(KL)expansion is the optimal series expansion method for random field discretization.The computational efficiency and accuracy of the KL expansion are contingent upon the accurate resolution of the Fredholm integral eigenvalue problem(IEVP).The paper proposes an interpolation method based on different interpolation basis functions such as moving least squares(MLS),least squares(LS),and finite element method(FEM)to solve the IEVP.Compared with the Galerkin method based on finite element or Legendre polynomials,the main advantage of the interpolation method is that,in the calculation of eigenvalues and eigenfunctions in one-dimensional random fields,the integral matrix containing covariance function only requires a single integral,which is less than a two-folded integral by the Galerkin method.The effectiveness and computational efficiency of the proposed interpolation method are verified through various one-dimensional examples.Furthermore,based on theKL expansion and polynomial chaos expansion,the stochastic analysis of two-dimensional regular and irregular domains is conducted,and the basis function of the extended finite element method(XFEM)is introduced as the interpolation basis function in two-dimensional irregular domains to solve the IEVP.
基金supported by Natural Science Foundation of Shandong ProvinceChina[ZR2022MH115]the National Natural Science Foundation of China[81301479,82202593]。
文摘Objective This study explored the potentially modifiable factors for depression and major depressive disorder(MDD)from the MR-Base database and further evaluated the associations between drug targets with MDD.Methods We analyzed two-sample of Mendelian randomization(2SMR)using genetic variant depression(n=113,154)and MDD(n=208,811)from Genome-Wide Association Studies(GWAS).Separate calculations were performed with modifiable risk factors from MR-Base for 1,001 genomes.The MR analysis was performed by screening drug targets with MDD in the DrugBank database to explore the therapeutic targets for MDD.Inverse variance weighted(IVW),fixed-effect inverse variance weighted(FE-IVW),MR-Egger,weighted median,and weighted mode were used for complementary calculation.Results The potential causal relationship between modifiable risk factors and depression contained 459 results for depression and 424 for MDD.Also,the associations between drug targets and MDD showed that SLC6A4,GRIN2A,GRIN2C,SCN10A,and IL1B expression are associated with an increased risk of depression.In contrast,ADRB1,CHRNA3,HTR3A,GSTP1,and GABRG2 genes are candidate protective factors against depression.Conclusion This study identified the risk factors causally associated with depression and MDD,and estimated 10 drug targets with significant impact on MDD,providing essential information for formulating strategies to prevent and treat depression.
基金supported by the National Natural Science Foundation of China under Grant(Number:52105136)the Hong Kong Scholar program under Grant(Number:XJ2022013)China Postdoctoral Science Foundation under Grant(Number:2021M690290)Academic Excellence Foundation of BUAA under Grant(Number:BY2004103).
文摘Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function,leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and accuracy.In this case,by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory,a random forest(RF)model is presented to enhance the computing efficiency of reliability degree;moreover,by embedding the RF model into multilevel optimization model,an efficient RF-assisted fatigue reliability-based design optimization framework is developed.Regarding the low-cycle fatigue reliability-based design optimization of aeroengine turbine disc as a case,the effectiveness of the presented framework is validated.The reliabilitybased design optimization results exhibit that the proposed framework holds high computing accuracy and computing efficiency.The current efforts shed a light on the theory/method development of reliability-based design optimization of complex engineering structures.
基金the National Key R&D Program of China(Nos.2018YFD0901506,2018YFD0900305)the Marine S&T Fund of Shandong Province for Pilot National Laboratory for Marine Science and Technology(Qingdao)(No.2018 SDKJ0406-3)。
文摘Insertional mutation,phenotypic evaluation,and mutated gene cloning are widely used to clone genes from scratch.Exogenous genes can be integrated into the genome during non-homologous end joining(NHEJ)of the double-strand breaks of DNA,causing insertional mutation.The random insertional mutant library constructed using this method has become a method of forward genetics for gene cloning.However,the establishment of a random insertional mutant library requires a high transformation efficiency of exogenous genes.Many microalgal species show a low transformation efficiency,making constructing random insertional mutant libraries difficult.In this study,we established a highly efficient transformation method for constructing a random insertional mutant library of Nannochloropsis oceanica,and tentatively tried to isolate its genes to prove the feasibility of the method.A gene that may control the growth rate and cell size was identified.This method will facilitate the genetic studies of N.oceanica,which should also be a reference for other microalgal species.
基金funded by the Nactional Natural Science Foundation of China(81872618)。
文摘Mental disorders seriously affect people’s health and social stability.This Mendelian randomization(MR)study was designed to investigate the causal relationship between circulating vitamin C(VC)or 25-hydroxyvitamin D(25(OH)D)levels and mental disorders.The data used for the MR analysis were derived from the summary genome-wide association studies(GWAS)database for VC and 25(OH)D and from the Finn Gen consortium for fourteen mental disorders.Based on the inverse variance weighted(IVW)method,we found a potential causal association between circulating VC and anxiety disorders(IVW:OR=1.139,95%CI:1.023-1.269,P=0.018).However,no causal association was found between VC or 25(OH)D and other mental disorders(P>0.05).In the reverse MR analysis,individuals with Alzheimer’s disease was causally associated with higher concentrations of circulating VC(P=0.012),while individuals with anxiety disorders had a negative association between the concentrations of 25(OH)D(P=0.012).However,the current evidence does not support a causal relationship between VC or 25(OH)D and other mental disorders.In addition,there was no causal association between circulating VC and 25(OH)D(P>0.05).Future studies are needed to confirm these findings and to elucidate the mechanisms of potential causality.
文摘The article introduces a finite element procedure using the bilinear quadrilateral element or four-node rectangular element(namely Q4 element) based on a refined first-order shear deformation theory(rFSDT) and Monte Carlo simulation(MCS), so-called refined stochastic finite element method to investigate the random vibration of functionally graded material(FGM) plates subjected to the moving load.The advantage of the proposed method is to use r-FSDT to improve the accuracy of classical FSDT, satisfy the stress-free condition at the plate boundaries, and combine with MCS to analyze the vibration of the FGM plate when the parameter inputs are random quantities following a normal distribution. The obtained results show that the distribution characteristics of the vibration response of the FGM plate depend on the standard deviation of the input parameters and the velocity of the moving load.Furthermore, the numerical results in this study are expected to contribute to improving the understanding of FGM plates subjected to moving loads with uncertain input parameters.
文摘BACKGROUND While the impact of depression on cognition is well-documented,the relationship between feelings and cognition has received limited attention.AIM To explore the potential association between feelings and cognition with a twosample Mendelian randomization(MR)analysis.METHODS Our analysis utilized genome-wide association data on various feelings(fed-up feelings,n=453071;worrier/anxious feelings,n=450765;guilty feelings,n=45-0704;nervous feelings,n=450700;sensitivity/hurt feelings,n=449419;miserableness,n=454982;loneliness/isolation,n=455364;happiness,n=152348)in the European population and their impact on cognitive functions(intelligence,n=269867).Conducting a univariable MR(UVMR)analysis to assess the relationship between feelings and cognition.In this analysis,we applied the inverse variance weighting(IVW),weighted median,and MR Egger methods.Additionally,we performed sensitivity analysis(leave-one-out analysis),assessed heterogeneity(using MR-PRESSO and Cochran’s Q test),and conducted multiple validity test(employing MR-Egger regression).Subsequently,a multivariable MR(MVMR)analysis was employed to examine the impact of feelings on cognition.IVW served as the primary method in the multivariable analysis,complemented by median-based and MR-Egger methods.RESULTS In this study,UVMR indicated that sensitivity/hurt feelings may have a negative causal effect on cognition(OR=0.63,95%CI:0.43-0.92,P=0.017).After adjustment of other feelings using MVMR,a direct adverse causal effect on cognition was observed(OR_(MVMR)=0.39,95%CI:0.17-0.90,P_(MVMR)=0.027).While a potential increased risk of cognitive decline was observed for fed-up feelings in the UVMR analysis(ORUVMR=0.64,95%CI:0.42-0.97,PUVMR=0.037),this effect disappeared after adjusting for other feelings(OR_(MVMR)=1.42,95%CI:0.43-4.74,P_(MVMR)=0.569).These findings were generally consistent across MV-IVW,median-based,and MR-Egger analyses.MR-Egger regression revealed pleiotropy in the impact of worrier/anxious feelings on cognition,presenting a challenge in identifying the effect.Notably,this study did not demonstrate any significant impact of guilty feelings,nervous feelings,miserableness,or loneliness/isolation on cognition.Due to a limited number of instrumental variables for happiness,this study was unable to analyze the relationship between happiness and cognition.CONCLUSION This MR study finds that sensitivity/hurt feelings are associated with cognitive decline,while the link between worrier/anxious feelings and cognition remains inconclusive.Insufficient evidence supports direct associations between happiness,guilty feelings,nervous feelings,miserableness,loneliness/isolation,and cognition.
基金supported by the MOE(Ministry of Education of China)Project of Humanities and Social Sciences(23YJAZH169)the Hubei Provincial Department of Education Outstanding Youth Scientific Innovation Team Support Foundation(T2020017)Henan Foreign Experts Project No.HNGD2023027.
文摘Image classification and unsupervised image segmentation can be achieved using the Gaussian mixture model.Although the Gaussian mixture model enhances the flexibility of image segmentation,it does not reflect spatial information and is sensitive to the segmentation parameter.In this study,we first present an efficient algorithm that incorporates spatial information into the Gaussian mixture model(GMM)without parameter estimation.The proposed model highlights the residual region with considerable information and constructs color saliency.Second,we incorporate the content-based color saliency as spatial information in the Gaussian mixture model.The segmentation is performed by clustering each pixel into an appropriate component according to the expectation maximization and maximum criteria.Finally,the random color histogram assigns a unique color to each cluster and creates an attractive color by default for segmentation.A random color histogram serves as an effective tool for data visualization and is instrumental in the creation of generative art,facilitating both analytical and aesthetic objectives.For experiments,we have used the Berkeley segmentation dataset BSDS-500 and Microsoft Research in Cambridge dataset.In the study,the proposed model showcases notable advancements in unsupervised image segmentation,with probabilistic rand index(PRI)values reaching 0.80,BDE scores as low as 12.25 and 12.02,compactness variations at 0.59 and 0.7,and variation of information(VI)reduced to 2.0 and 1.49 for the BSDS-500 and MSRC datasets,respectively,outperforming current leading-edge methods and yielding more precise segmentations.
基金supported by Zhejiang Provincial Natural Science Foundation of China(LR20A010001)National Natural Science Foundation of China(12271473 and U21A20426)。
文摘In the realm of large-scale machine learning,it is crucial to explore methods for reducing computational complexity and memory demands while maintaining generalization performance.Additionally,since the collected data may contain some sensitive information,it is also of great significance to study privacy-preserving machine learning algorithms.This paper focuses on the performance of the differentially private stochastic gradient descent(SGD)algorithm based on random features.To begin,the algorithm maps the original data into a lowdimensional space,thereby avoiding the traditional kernel method for large-scale data storage requirement.Subsequently,the algorithm iteratively optimizes parameters using the stochastic gradient descent approach.Lastly,the output perturbation mechanism is employed to introduce random noise,ensuring algorithmic privacy.We prove that the proposed algorithm satisfies the differential privacy while achieving fast convergence rates under some mild conditions.
