The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction ...The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction fuse actuator.The impact point easily deviates from the target,and thus the correction result cannot be readily evaluated.However,the cost of shooting tests is considerably high to conduct many tests for data collection.To address this issue,this study proposes an aiming method for shooting tests based on small sample size.The proposed method uses the Bootstrap method to expand the test data;repeatedly iterates and corrects the position of the simulated theoretical impact points through an improved compatibility test method;and dynamically adjusts the weight of the prior distribution of simulation results based on Kullback-Leibler divergence,which to some extent avoids the real data being"submerged"by the simulation data and achieves the fusion Bayesian estimation of the dispersion center.The experimental results show that when the simulation accuracy is sufficiently high,the proposed method yields a smaller mean-square deviation in estimating the dispersion center and higher shooting accuracy than those of the three comparison methods,which is more conducive to reflecting the effect of the control algorithm and facilitating test personnel to iterate their proposed structures and algorithms.;in addition,this study provides a knowledge base for further comprehensive studies in the future.展开更多
Sample size determination typically relies on a power analysis based on a frequentist conditional approach. This latter can be seen as a particular case of the two-priors approach, which allows to build four distinct ...Sample size determination typically relies on a power analysis based on a frequentist conditional approach. This latter can be seen as a particular case of the two-priors approach, which allows to build four distinct power functions to select the optimal sample size. We revise this approach when the focus is on testing a single binomial proportion. We consider exact methods and introduce a conservative criterion to account for the typical non-monotonic behavior of the power functions, when dealing with discrete data. The main purpose of this paper is to present a Shiny App providing a user-friendly, interactive tool to apply these criteria. The app also provides specific tools to elicit the analysis and the design prior distributions, which are the core of the two-priors approach.展开更多
Reliability assessment of the braking system in a high?speed train under small sample size and zero?failure data is veryimportant for safe operation. Traditional reliability assessment methods are only performed well ...Reliability assessment of the braking system in a high?speed train under small sample size and zero?failure data is veryimportant for safe operation. Traditional reliability assessment methods are only performed well under conditions of large sample size and complete failure data,which lead to large deviation under conditions of small sample size and zero?failure data. To improve this problem,a new Bayesian method is proposed. Based on the characteristics of the solenoid valve in the braking system of a high?speed train,the modified Weibull distribution is selected to describe the failure rate over the entire lifetime. Based on the assumption of a binomial distribution for the failure probability at censored time,a concave method is employed to obtain the relationships between accumulation failure prob?abilities. A numerical simulation is performed to compare the results of the proposed method with those obtained from maximum likelihood estimation,and to illustrate that the proposed Bayesian model exhibits a better accuracy for the expectation value when the sample size is less than 12. Finally,the robustness of the model is demonstrated by obtaining the reliability indicators for a numerical case involving the solenoid valve of the braking system,which shows that the change in the reliability and failure rate among the di erent hyperparameters is small. The method is provided to avoid misleading of subjective information and improve accuracy of reliability assessment under condi?tions of small sample size and zero?failure data.展开更多
The development of a core collection could enhance the utilization of germplasm collections in crop improvement programs and simplify their management. Selection of an appropriate sampling strategy is an important pre...The development of a core collection could enhance the utilization of germplasm collections in crop improvement programs and simplify their management. Selection of an appropriate sampling strategy is an important prerequisite to construct a core collection with appropriate size in order to adequately represent the genetic spectrum and maximally capture the genetic diversity in available crop collections. The present study was initiated to construct nested core collections to determine the appropriate sample size to represent the genetic diversity of rice landrace collection based on 15 quantitative traits and 34 qualitative traits of 2 262 rice accessions. The results showed that 50-225 nested core collections, whose sampling rate was 2.2%-9.9%, were sufficient to maintain the maximum genetic diversity of the initial collections. Of these, 150 accessions （6.6%） could capture the maximal genetic diversity of the initial collection. Three data types, i.e. qualitative traits （QT1）, quantitative traits （QT2） and integrated qualitative and quantitative traits （QTT）, were compared for their efficiency in constructing core collections based on the weighted pair-group average method combined with stepwise clustering and preferred sampling on adjusted Euclidean distances. Every combining scheme constructed eight rice core collections （225, 200, 175, 150, 125, 100, 75 and 50）. The results showed that the QTT data was the best in constructing a core collection as indicated by the genetic diversity of core collections. A core collection constructed only on the information of QT1 could not represent the initial collection effectively. QTT should be used together to construct a productive core collection.展开更多
In order to investigate the effect of sample size on the dynamic torsional behaviour of the 2A12 aluminium alloy. In this paper, torsional split Hopkinson bar tests are conducted on this alloy with different sample di...In order to investigate the effect of sample size on the dynamic torsional behaviour of the 2A12 aluminium alloy. In this paper, torsional split Hopkinson bar tests are conducted on this alloy with different sample dimensions. It is found that with the decreasing gauge length and thickness, the tested yield strength increases. However, the sample innerlouter diameter has little effect on the dynamic torsional behaviour. Based on the finite element method, the stress states in the alloy with different sample sizes are analysed. Due to the effect of stress concentration zone （SCZ）, the shorter sample has a higher yield stress. Furthermore, the stress distributes more uniformly in the thinner sample, which leads to the higher tested yield stress. According to the experimental and simulation analysis, some suggestions on choosing the sample size are given as well.展开更多
In the October 2014 publication of JAMA,Dr.Hinman and colleagues published the study＂Acupuncture for Chronic Knee Pain：A Randomized Clinical Trial,＂in which the authors concluded that＂in patients older than50 year...In the October 2014 publication of JAMA,Dr.Hinman and colleagues published the study＂Acupuncture for Chronic Knee Pain：A Randomized Clinical Trial,＂in which the authors concluded that＂in patients older than50 years with moderate or severe chronic knee pain,neither laser nor needle acupuncture conferred benefi t over sham for pain or function.Our fi ndings do not support acupuncture[1]展开更多
This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into t...This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into three categories:(1) direct indices, like the trophic level of species, influenced by stomach sample size directly;(2)indirect indices, like ecology efficiency(EE) of invertebrates, influenced by the multiple prey-predator relationships;and(3) systemic indices, like total system throughout(TST), describing the status of the whole ecosystem. The influences of different stomach sample sizes on these indices were evaluated. The results suggest that systemic indices of the ecosystem model were robust to stomach sample sizes, whereas specific indices related to species were indicated to be with low accuracy and precision when stomach samples were insufficient.The indices became more uncertain when the stomach sample sizes varied for more species. This study enhances the understanding of how the quality of diet composition data influences ecosystem modeling outputs. The results can also guide the design of stomach content analysis for developing ecosystem models.展开更多
Sample size re-estimation is essential in oncology studies. However, the use of blinded sample size reassessment for survival data has been rarely reported. Based on the density function of the exponential distributio...Sample size re-estimation is essential in oncology studies. However, the use of blinded sample size reassessment for survival data has been rarely reported. Based on the density function of the exponential distribution, an expectation-maximization（EM） algorithm of the hazard ratio was derived, and several simulation studies were used to verify its applications. The method had obvious variation in the hazard ratio estimates and overestimation for the relatively small hazard ratios. Our studies showed that the stability of the EM estimation results directly correlated with the sample size, the convergence of the EM algorithm was impacted by the initial values, and a balanced design produced the best estimates. No reliable blinded sample size re-estimation inference can be made in our studies, but the results provide useful information to steer the practitioners in this field from repeating the same endeavor.展开更多
The precise and accurate knowledge of genetic parameters is a prerequisite for making efficient selection strategies in breeding programs.A number of estimators of heritability about important economic traits in many ...The precise and accurate knowledge of genetic parameters is a prerequisite for making efficient selection strategies in breeding programs.A number of estimators of heritability about important economic traits in many marine mollusks are available in the literature,however very few research have evaluated about the accuracy of genetic parameters estimated with different family structures.Thus,in the present study,the effect of parent sample size for estimating the precision of genetic parameters of four growth traits in clam M.meretrix by factorial designs were analyzed through restricted maximum likelihood（REML） and Bayesian.The results showed that the average estimated heritabilities of growth traits obtained from REML were 0.23-0.32 for 9 and 16 full-sib families and 0.19-0.22 for 25 full-sib families.When using Bayesian inference,the average estimated heritabilities were0.11-0.12 for 9 and 16 full-sib families and 0.13-0.16 for 25 full-sib families.Compared with REML,Bayesian got lower heritabilities,but still remained at a medium level.When the number of parents increased from 6 to 10,the estimated heritabilities were more closed to 0.20 in REML and 0.12 in Bayesian inference.Genetic correlations among traits were positive and high and had no significant difference between different sizes of designs.The accuracies of estimated breeding values from the 9 and 16 families were less precise than those from 25 families.Our results provide a basic genetic evaluation for growth traits and should be useful for the design and operation of a practical selective breeding program in the clam M.meretrix.展开更多
BACKGROUND Of 25%of randomised controlled trials(RCTs)on interventions for inflammatory bowel disease(IBD)have no power calculation.AIM To systematically review RCTs reporting interventions for the management of IBD a...BACKGROUND Of 25%of randomised controlled trials(RCTs)on interventions for inflammatory bowel disease(IBD)have no power calculation.AIM To systematically review RCTs reporting interventions for the management of IBD and to produce data for minimum sample sizes that would achieve appropriate power using the actual clinical data.METHODS We included RCTs retrieved from Cochrane IBD specialised Trial register and CENTRAL investigating any form of therapy for either induction or maintenance of remission against control,placebo,or no intervention of IBD in patients of any age.The relevant data was extracted,and the studies were grouped according to the intervention used.We recalculated sample size and the achieved difference,as well as minimum sample sizes needed in the future.RESULTS A total of 105 trials were included.There was a large discrepancy between the estimated figure for the minimal clinically important difference used for the calculations(15%group differences observed vs 30%used for calculation)explaining substantial actual sample size deficits.The minimum sample sizes indicated for future trials based on the 25 years of trial data were calculated and grouped by the intervention.CONCLUSION A third of intervention studies in IBD within the last 25 years are underpowered,with large variations in the calculation of sample sizes.The authors present a sample size estimate resource constructed on the published evidence base for future researchers and key stakeholders within the IBD trial field.展开更多
To clarify the most appropriate sample size for obtaining phenotypic data for a single line,we investigated the main-effect QTL(M-QTL) of a quantitative trait plant height(ph) in a recombinant inbred line(RIL) populat...To clarify the most appropriate sample size for obtaining phenotypic data for a single line,we investigated the main-effect QTL(M-QTL) of a quantitative trait plant height(ph) in a recombinant inbred line(RIL) population of rice(derived from the cross between Xieqingzao B and Zhonghui 9308) using five individual plants in 2006 and 2009.Twenty-six ph phenotypic datasets from the completely random combinations of 2,3,4,and 5 plants in a single line,and five ph phenotypic datasets from five individual plants were used to detect the QTLs.Fifteen M-QTLs were detected by 1 to 31 datasets.Of these,qph7a was detected repeatedly by all the 31 ph datasets in 2006 and explained 11.67% to 23.93% of phenotypic variation;qph3 was detected repeatedly by all the 31 datasets and explained 5.21% to 7.93% and 11.51% to 24.46% of phenotypic variance in 2006 and 2009,respectively.The results indicate that the M-QTL for a quantitative trait could be detected repeatedly by the phenotypic values from 5 individual plants and 26 sets of completely random combinations of phenotypic data within a single line in an RIL population under different environments.The sample size for a single line of the RIL population did not affect the efficiency for identification of stably expressed M-QTLs.展开更多
After finishing 102 replicate constant amplitude crack initiation and growth tests on Ly12-CZ aluminum alloy plate, a statistical investigation of the fatigue crack initiation and growth process is conducted in this p...After finishing 102 replicate constant amplitude crack initiation and growth tests on Ly12-CZ aluminum alloy plate, a statistical investigation of the fatigue crack initiation and growth process is conducted in this paper. According to the post-mortem fractographic examination by scanning electron microscopy (SEM), some qualitative observations of the spacial correlation among fatigue striations are developed to reveal the statistical nature of material intrinsic inhomogeneity during the crack growth process. From the test data, an engineering division between crack initiation and growth is defined as the upper limit of small crack. The distributions of crack initiation life N-i, growth life N, and the statistical characteristics of crack growth rate da/dN are also investigated. It is hoped that the work will provide a solid test basis for the study of probabilistic fatigue, probabilistic fracture mechanics, fatigue reliability and its engineering applications.展开更多
Sample size can be a key design feature that not only affects the probability of a trial＇s success but also determines the duration and feasibility of a trial. If an investigational drug is expected to be effective a...Sample size can be a key design feature that not only affects the probability of a trial＇s success but also determines the duration and feasibility of a trial. If an investigational drug is expected to be effective and address unmet medical needs of an orphan disease, where the accrual period may require many years with a large sample size to detect a minimal clinically relevant treatment effect, a minimum sample size may be set to maintain nominal power. In limited situations such as this, there may be a need for flexibility in the initial and final sample sizes; thus, it is useful to consider the utility of adaptive sample size designs that use sample size re-estimation or group sequential design. In this paper, we propose a new adaptive performance measure to consider the utility of an adaptive sample size design in a trial simulation. Considering that previously proposed sample size re-estimation methods do not take into account errors in estimation based on interim results, we propose Bayesian sample size re-estimation criteria that take into account prior information on treatment effect, and then, we assess its operating characteristics in a simulation study. We also present a review example of sample size re-estimation mainly based on published paper and review report in Pharmaceuticals and Medical Devices Agency （PMDA）.展开更多
Knowledge on spatial distribution and sampling size optimization of soil copper （Cu） could lay solid foundations for environmetal quality survey of agricultural soils at county scale. In this investigation, cokrigin...Knowledge on spatial distribution and sampling size optimization of soil copper （Cu） could lay solid foundations for environmetal quality survey of agricultural soils at county scale. In this investigation, cokriging method was used to conduct the interpolation of Cu concentraiton in cropland soil in Shuangliu County, Sichuan Province, China. Based on the original 623 physicochmically measured soil samples, 560, 498, and 432 sub-samples were randomly selected as target variable and soil organic matter （SOM） of the whole original samples as auxiliary variable. Interpolation results using Cokriging under different sampling numbers were evaluated for their applicability in estimating the spatial distribution of soil Cu at county sacle. The results showed that the root mean square error （RMSE） produced by Cokriging decreased from 0.9 to 7.77%, correlation coefficient between the predicted values and the measured increased from 1.76 to 9.76% in comparison with the ordinary Kriging under the corresponding sample sizes. The prediction accuracy using Cokriging was still higher than original 623 data using ordinary Kriging even as sample size reduced 10%, and their interpolation maps were highly in agreement. Therefore, Cokriging was proven to be a more accurate and economic method which could provide more information and benefit for the studies on spatial distribution of soil pollutants at county scale.展开更多
Machine learning (ML) has been widely used todesign and develop new materials owing to its low computational cost and powerful predictive capabilities. In recentyears, the shortcomings of ML in materials science have ...Machine learning (ML) has been widely used todesign and develop new materials owing to its low computational cost and powerful predictive capabilities. In recentyears, the shortcomings of ML in materials science have gradually emerged, with a primary concern being the scarcity ofdata. It is challenging to build reliable and accurate ML modelsusing limited data. Moreover, the small sample size problemwill remain long-standing in materials science because of theslow accumulation of material data. Therefore, it is importantto review and categorize strategies for small-sample learningfor the development of ML in materials science. This reviewsystematically sorts the research progress of small-samplelearning strategies in materials science, including ensemblelearning, unsupervised learning, active learning, and transferlearning. The directions for future research are proposed, including few-shot learning, and virtual sample generation.More importantly, we emphasize the significance of embedding material domain knowledge into ML and elaborate on thebasic idea for implementing this strategy.展开更多
Surface/underwater target classification is a key topic in marine information research.However,the complex underwater environment,coupled with the diversity of target types and their variable characteristics,presents ...Surface/underwater target classification is a key topic in marine information research.However,the complex underwater environment,coupled with the diversity of target types and their variable characteristics,presents significant challenges for classifier design.For shallow-water waveguides with a negative thermocline,a residual neural network(ResNet)model based on the sound field elevation structure is constructed.This model demonstrates robust classification performance even when facing low signal-to-noise ratios and environmental mismatches.Meanwhile,to address the reduced generalization ability caused by limited labeled acoustic data,an improved ResNet model based on unsupervised domain adaptation(“proposed UDA-ResNet”)is further constructed.This model incorporates data on simulated elevation structures of the sound field to augment the training process.Adversarial training is employed to extract domain-invariant features from simulated and trial data.These strategies help reduce the negative impact caused by domain differences.Experimental results demonstrate that the proposed method shows strong surface/underwater target classification ability under limited sample sizes,thus confirming its feasibility and effectiveness.展开更多
Random sample partition(RSP)is a newly developed big data representation and management model to deal with big data approximate computation problems.Academic research and practical applications have confirmed that RSP...Random sample partition(RSP)is a newly developed big data representation and management model to deal with big data approximate computation problems.Academic research and practical applications have confirmed that RSP is an efficient solution for big data processing and analysis.However,a challenge for implementing RSP is determining an appropriate sample size for RSP data blocks.While a large sample size increases the burden of big data computation,a small size will lead to insufficient distribution information for RSP data blocks.To address this problem,this paper presents a novel density estimation-based method(DEM)to determine the optimal sample size for RSP data blocks.First,a theoretical sample size is calculated based on the multivariate Dvoretzky-Kiefer-Wolfowitz(DKW)inequality by using the fixed-point iteration(FPI)method.Second,a practical sample size is determined by minimizing the validation error of a kernel density estimator(KDE)constructed on RSP data blocks for an increasing sample size.Finally,a series of persuasive experiments are conducted to validate the feasibility,rationality,and effectiveness of DEM.Experimental results show that(1)the iteration function of the FPI method is convergent for calculating the theoretical sample size from the multivariate DKW inequality;(2)the KDE constructed on RSP data blocks with sample size determined by DEM can yield a good approximation of the probability density function(p.d.f);and(3)DEM provides more accurate sample sizes than the existing sample size determination methods from the perspective of p.d.f.estimation.This demonstrates that DEM is a viable approach to deal with the sample size determination problem for big data RSP implementation.展开更多
The sap flow method is widely used to estimate forest transpiration.However,at the individual tree level it has spatiotemporal variations due to the impacts of environmental conditions and spatial relationships among ...The sap flow method is widely used to estimate forest transpiration.However,at the individual tree level it has spatiotemporal variations due to the impacts of environmental conditions and spatial relationships among trees.Therefore,an in-depth understanding of the coupling effects of these factors is important for designing sap flow measurement methods and performing accurate assessments of stand scale transpiration.This study is based on observations of sap flux density(SF_(d))of nine sample trees with different Hegyi’s competition indices(HCIs),soil moisture,and meteorological conditions in a pure plantation of Larix gmelinii var.principis-rupprechtii during the 2021 growing season(May to September).A multifactorial model of sap flow was developed and possible errors in the stand scale sap flow estimates associated with sample sizes were determined using model-based predictions of sap flow.Temporal variations are controlled by vapour pressure deficit(VPD),solar radiation(R),and soil moisture,and these relationships can be described by polynomial or saturated exponential functions.Spatial(individual)differences were influenced by the HCI,as shown by the decaying power function.A simple SF_(d)model at the individual tree level was developed to describe the synergistic influences of VPD,R,soil moisture,and HCI.The coefficient of variations(CV)of the sap flow estimates gradually stabilized when the sample size was>10;at least six sample trees were needed if the CV was within 10%.This study improves understanding of the mechanisms of spatiotemporal variations in sap flow at the individual tree level and provides a new methodology for determining the optimal sample size for sap flow measurements.展开更多
Plant species diversity is one of the most widely used indicators in ecosystem management.The relation of species diversity with the size of the sample plot has not been fully determined for Oriental beech forests(Fag...Plant species diversity is one of the most widely used indicators in ecosystem management.The relation of species diversity with the size of the sample plot has not been fully determined for Oriental beech forests(Fagus orientalis Lipsky),a widespread species in the Hyrcanian region.Assessing the impacts of plot size on species diversity is fundamental for an ecosystem-based approach to forest management.This study determined the relation of species diversity and plot size by investigating species richness and abundance of both canopy and forest floor.Two hundred and fifty-six sample plots of 625 m^(2) each were layout in a grid pattern across 16 ha.Base plots(25 m×25 m)were integrated in different scales to investigate the effect of plot size on species diversity.The total included nine plots of 0.063,0.125,0.188,0.250,0.375,0.500,0.563,0.750 and 1 ha.Ten biodiversity indices were calculated.The results show that species richness in the different plot sizes was less than the actual value.The estimated value of the Simpson species diversity index was not significantly different from actual values for both canopy and forest floor diversity.The coefficient of variation of this index for the 1-ha sample plot showed the lowest amount across different plot sizes.Inverse Hill species diversity was insignificant difference across different plot sizes with an area greater than 0.500 ha.The modified Hill evenness index for the 1-ha sample size was a correct estimation of the 16-ha for both canopy and forest floor;however,the precision estimation was higher for the canopy layer.All plots greater than 0.250-ha provided an accurate estimation of the Camargo evenness index for forest floor species,but was inaccurate across different plot sizes for the canopy layer.The results indicate that the same plot size did not have the same effect across species diversity measurements.Our results show that correct estimation of species diversity measurements is related to the selection of appropriate indicators and plot size to increase the accuracy of the estimate so that the cost and time of biodiversity management may be reduced.展开更多
This paper shows that for DEM simulations of triaxial tests using samples with a grading that is repre- sentative of a real soil, the sample size significantly influences the observed material response. Four DEM sampl...This paper shows that for DEM simulations of triaxial tests using samples with a grading that is repre- sentative of a real soil, the sample size significantly influences the observed material response. Four DEM samples with identical initial states were produced： three cylindrical samples bounded by rigid wails and one bounded by a cubical periodic cell, When subjected to triaxial loading, the samples with rigid boundaries were more dilative, stiffer and reached a higher peak stress ratio than the sample enclosed by periodic boundaries. For the rigid-wall samples, dilatancy increased and stiffness decreased with increasing sample size, The periodic sample was effectively homogeneous, The void ratio increased and the contact density decreased close to the rigid walls, This heterogeneity reduced with increasing sample size. The positions of the critical state lines （CSLs） of the overall response in e-log p＇ space were sensitive to the sample size, although no difference was observed between their slopes. The critical states of the interior regions of the rigid-wall-bounded samples approached that of the homogeneous periodic sample with increasing sample size. The ultimate strength of the material at the critical state is independent of sample size.展开更多
基金the National Natural Science Foundation of China(Grant No.61973033)Preliminary Research of Equipment(Grant No.9090102010305)for funding the experiments。
文摘The longitudinal dispersion of the projectile in shooting tests of two-dimensional trajectory corrections fused with fixed canards is extremely large that it sometimes exceeds the correction ability of the correction fuse actuator.The impact point easily deviates from the target,and thus the correction result cannot be readily evaluated.However,the cost of shooting tests is considerably high to conduct many tests for data collection.To address this issue,this study proposes an aiming method for shooting tests based on small sample size.The proposed method uses the Bootstrap method to expand the test data;repeatedly iterates and corrects the position of the simulated theoretical impact points through an improved compatibility test method;and dynamically adjusts the weight of the prior distribution of simulation results based on Kullback-Leibler divergence,which to some extent avoids the real data being"submerged"by the simulation data and achieves the fusion Bayesian estimation of the dispersion center.The experimental results show that when the simulation accuracy is sufficiently high,the proposed method yields a smaller mean-square deviation in estimating the dispersion center and higher shooting accuracy than those of the three comparison methods,which is more conducive to reflecting the effect of the control algorithm and facilitating test personnel to iterate their proposed structures and algorithms.;in addition,this study provides a knowledge base for further comprehensive studies in the future.
文摘Sample size determination typically relies on a power analysis based on a frequentist conditional approach. This latter can be seen as a particular case of the two-priors approach, which allows to build four distinct power functions to select the optimal sample size. We revise this approach when the focus is on testing a single binomial proportion. We consider exact methods and introduce a conservative criterion to account for the typical non-monotonic behavior of the power functions, when dealing with discrete data. The main purpose of this paper is to present a Shiny App providing a user-friendly, interactive tool to apply these criteria. The app also provides specific tools to elicit the analysis and the design prior distributions, which are the core of the two-priors approach.
基金Supported by National Natural Science Foundation of China(Grant No.51175028)Great Scholars Training Project(Grant No.CIT&TCD20150312)Beijing Recognized Talent Project(Grant No.2014018)
文摘Reliability assessment of the braking system in a high?speed train under small sample size and zero?failure data is veryimportant for safe operation. Traditional reliability assessment methods are only performed well under conditions of large sample size and complete failure data,which lead to large deviation under conditions of small sample size and zero?failure data. To improve this problem,a new Bayesian method is proposed. Based on the characteristics of the solenoid valve in the braking system of a high?speed train,the modified Weibull distribution is selected to describe the failure rate over the entire lifetime. Based on the assumption of a binomial distribution for the failure probability at censored time,a concave method is employed to obtain the relationships between accumulation failure prob?abilities. A numerical simulation is performed to compare the results of the proposed method with those obtained from maximum likelihood estimation,and to illustrate that the proposed Bayesian model exhibits a better accuracy for the expectation value when the sample size is less than 12. Finally,the robustness of the model is demonstrated by obtaining the reliability indicators for a numerical case involving the solenoid valve of the braking system,which shows that the change in the reliability and failure rate among the di erent hyperparameters is small. The method is provided to avoid misleading of subjective information and improve accuracy of reliability assessment under condi?tions of small sample size and zero?failure data.
基金supported by the National Natural Science Foundation of China (Grant No. 30700494)the Principal Fund of South China Agricultural University, China (Grant No. 2003K053)
文摘The development of a core collection could enhance the utilization of germplasm collections in crop improvement programs and simplify their management. Selection of an appropriate sampling strategy is an important prerequisite to construct a core collection with appropriate size in order to adequately represent the genetic spectrum and maximally capture the genetic diversity in available crop collections. The present study was initiated to construct nested core collections to determine the appropriate sample size to represent the genetic diversity of rice landrace collection based on 15 quantitative traits and 34 qualitative traits of 2 262 rice accessions. The results showed that 50-225 nested core collections, whose sampling rate was 2.2%-9.9%, were sufficient to maintain the maximum genetic diversity of the initial collections. Of these, 150 accessions （6.6%） could capture the maximal genetic diversity of the initial collection. Three data types, i.e. qualitative traits （QT1）, quantitative traits （QT2） and integrated qualitative and quantitative traits （QTT）, were compared for their efficiency in constructing core collections based on the weighted pair-group average method combined with stepwise clustering and preferred sampling on adjusted Euclidean distances. Every combining scheme constructed eight rice core collections （225, 200, 175, 150, 125, 100, 75 and 50）. The results showed that the QTT data was the best in constructing a core collection as indicated by the genetic diversity of core collections. A core collection constructed only on the information of QT1 could not represent the initial collection effectively. QTT should be used together to construct a productive core collection.
基金Financial support is from the NSFC(Grant Nos.11602257,11472257,11272300,11572299)funded by the key subject"Computational Solid Mechanics"of the China Academy of Engineering Physics
文摘In order to investigate the effect of sample size on the dynamic torsional behaviour of the 2A12 aluminium alloy. In this paper, torsional split Hopkinson bar tests are conducted on this alloy with different sample dimensions. It is found that with the decreasing gauge length and thickness, the tested yield strength increases. However, the sample innerlouter diameter has little effect on the dynamic torsional behaviour. Based on the finite element method, the stress states in the alloy with different sample sizes are analysed. Due to the effect of stress concentration zone （SCZ）, the shorter sample has a higher yield stress. Furthermore, the stress distributes more uniformly in the thinner sample, which leads to the higher tested yield stress. According to the experimental and simulation analysis, some suggestions on choosing the sample size are given as well.
文摘In the October 2014 publication of JAMA,Dr.Hinman and colleagues published the study＂Acupuncture for Chronic Knee Pain：A Randomized Clinical Trial,＂in which the authors concluded that＂in patients older than50 years with moderate or severe chronic knee pain,neither laser nor needle acupuncture conferred benefi t over sham for pain or function.Our fi ndings do not support acupuncture[1]
基金The National Natural Science Foundation of China under contract No.31772852the Fundamental Research Funds for the Central Universities under contract No.201612004。
文摘This study used Ecopath model of the Jiaozhou Bay as an example to evaluate the effect of stomach sample size of three fish species on the projection of this model. The derived ecosystem indices were classified into three categories:(1) direct indices, like the trophic level of species, influenced by stomach sample size directly;(2)indirect indices, like ecology efficiency(EE) of invertebrates, influenced by the multiple prey-predator relationships;and(3) systemic indices, like total system throughout(TST), describing the status of the whole ecosystem. The influences of different stomach sample sizes on these indices were evaluated. The results suggest that systemic indices of the ecosystem model were robust to stomach sample sizes, whereas specific indices related to species were indicated to be with low accuracy and precision when stomach samples were insufficient.The indices became more uncertain when the stomach sample sizes varied for more species. This study enhances the understanding of how the quality of diet composition data influences ecosystem modeling outputs. The results can also guide the design of stomach content analysis for developing ecosystem models.
基金supported by the National Natural Science Foundation of China(81273184)the National Natural Science Foundation of China Grant for Young Scientists (81302512)
文摘Sample size re-estimation is essential in oncology studies. However, the use of blinded sample size reassessment for survival data has been rarely reported. Based on the density function of the exponential distribution, an expectation-maximization（EM） algorithm of the hazard ratio was derived, and several simulation studies were used to verify its applications. The method had obvious variation in the hazard ratio estimates and overestimation for the relatively small hazard ratios. Our studies showed that the stability of the EM estimation results directly correlated with the sample size, the convergence of the EM algorithm was impacted by the initial values, and a balanced design produced the best estimates. No reliable blinded sample size re-estimation inference can be made in our studies, but the results provide useful information to steer the practitioners in this field from repeating the same endeavor.
基金The National High Technology Research and Development Program(863 program)of China under contract No.2012AA10A410the Zhejiang Science and Technology Project of Agricultural Breeding under contract No.2012C12907-4the Scientific and Technological Innovation Project financially supported by Qingdao National Laboratory for Marine Science and Technology under contract No.2015ASKJ02
文摘The precise and accurate knowledge of genetic parameters is a prerequisite for making efficient selection strategies in breeding programs.A number of estimators of heritability about important economic traits in many marine mollusks are available in the literature,however very few research have evaluated about the accuracy of genetic parameters estimated with different family structures.Thus,in the present study,the effect of parent sample size for estimating the precision of genetic parameters of four growth traits in clam M.meretrix by factorial designs were analyzed through restricted maximum likelihood（REML） and Bayesian.The results showed that the average estimated heritabilities of growth traits obtained from REML were 0.23-0.32 for 9 and 16 full-sib families and 0.19-0.22 for 25 full-sib families.When using Bayesian inference,the average estimated heritabilities were0.11-0.12 for 9 and 16 full-sib families and 0.13-0.16 for 25 full-sib families.Compared with REML,Bayesian got lower heritabilities,but still remained at a medium level.When the number of parents increased from 6 to 10,the estimated heritabilities were more closed to 0.20 in REML and 0.12 in Bayesian inference.Genetic correlations among traits were positive and high and had no significant difference between different sizes of designs.The accuracies of estimated breeding values from the 9 and 16 families were less precise than those from 25 families.Our results provide a basic genetic evaluation for growth traits and should be useful for the design and operation of a practical selective breeding program in the clam M.meretrix.
文摘BACKGROUND Of 25%of randomised controlled trials(RCTs)on interventions for inflammatory bowel disease(IBD)have no power calculation.AIM To systematically review RCTs reporting interventions for the management of IBD and to produce data for minimum sample sizes that would achieve appropriate power using the actual clinical data.METHODS We included RCTs retrieved from Cochrane IBD specialised Trial register and CENTRAL investigating any form of therapy for either induction or maintenance of remission against control,placebo,or no intervention of IBD in patients of any age.The relevant data was extracted,and the studies were grouped according to the intervention used.We recalculated sample size and the achieved difference,as well as minimum sample sizes needed in the future.RESULTS A total of 105 trials were included.There was a large discrepancy between the estimated figure for the minimal clinically important difference used for the calculations(15%group differences observed vs 30%used for calculation)explaining substantial actual sample size deficits.The minimum sample sizes indicated for future trials based on the 25 years of trial data were calculated and grouped by the intervention.CONCLUSION A third of intervention studies in IBD within the last 25 years are underpowered,with large variations in the calculation of sample sizes.The authors present a sample size estimate resource constructed on the published evidence base for future researchers and key stakeholders within the IBD trial field.
基金supported by the grants from the Chinese Natural Science Foundation(Grant No.31071398)the National Program on Super Rice Breeding,the Ministry of Agriculture(Grant No.2010-3)+1 种基金National High Technology Research and Development Program of China(Grant No.2006AA10Z1E8)the Provincial Program of ‘8812’,Zhejiang Province,China(Grant No.8812-1)
文摘To clarify the most appropriate sample size for obtaining phenotypic data for a single line,we investigated the main-effect QTL(M-QTL) of a quantitative trait plant height(ph) in a recombinant inbred line(RIL) population of rice(derived from the cross between Xieqingzao B and Zhonghui 9308) using five individual plants in 2006 and 2009.Twenty-six ph phenotypic datasets from the completely random combinations of 2,3,4,and 5 plants in a single line,and five ph phenotypic datasets from five individual plants were used to detect the QTLs.Fifteen M-QTLs were detected by 1 to 31 datasets.Of these,qph7a was detected repeatedly by all the 31 ph datasets in 2006 and explained 11.67% to 23.93% of phenotypic variation;qph3 was detected repeatedly by all the 31 datasets and explained 5.21% to 7.93% and 11.51% to 24.46% of phenotypic variance in 2006 and 2009,respectively.The results indicate that the M-QTL for a quantitative trait could be detected repeatedly by the phenotypic values from 5 individual plants and 26 sets of completely random combinations of phenotypic data within a single line in an RIL population under different environments.The sample size for a single line of the RIL population did not affect the efficiency for identification of stably expressed M-QTLs.
基金The project is supported by the Aeronautic Science Foundation,China
文摘After finishing 102 replicate constant amplitude crack initiation and growth tests on Ly12-CZ aluminum alloy plate, a statistical investigation of the fatigue crack initiation and growth process is conducted in this paper. According to the post-mortem fractographic examination by scanning electron microscopy (SEM), some qualitative observations of the spacial correlation among fatigue striations are developed to reveal the statistical nature of material intrinsic inhomogeneity during the crack growth process. From the test data, an engineering division between crack initiation and growth is defined as the upper limit of small crack. The distributions of crack initiation life N-i, growth life N, and the statistical characteristics of crack growth rate da/dN are also investigated. It is hoped that the work will provide a solid test basis for the study of probabilistic fatigue, probabilistic fracture mechanics, fatigue reliability and its engineering applications.
文摘Sample size can be a key design feature that not only affects the probability of a trial＇s success but also determines the duration and feasibility of a trial. If an investigational drug is expected to be effective and address unmet medical needs of an orphan disease, where the accrual period may require many years with a large sample size to detect a minimal clinically relevant treatment effect, a minimum sample size may be set to maintain nominal power. In limited situations such as this, there may be a need for flexibility in the initial and final sample sizes; thus, it is useful to consider the utility of adaptive sample size designs that use sample size re-estimation or group sequential design. In this paper, we propose a new adaptive performance measure to consider the utility of an adaptive sample size design in a trial simulation. Considering that previously proposed sample size re-estimation methods do not take into account errors in estimation based on interim results, we propose Bayesian sample size re-estimation criteria that take into account prior information on treatment effect, and then, we assess its operating characteristics in a simulation study. We also present a review example of sample size re-estimation mainly based on published paper and review report in Pharmaceuticals and Medical Devices Agency （PMDA）.
基金supported by the Youth Foundation from Sichuan Education Bureau (2006B009)Key Project from Sichuan Education Bureau (2006A008)Sichuan Youth Science & Technology Foundation,China (06ZQ026-020)
文摘Knowledge on spatial distribution and sampling size optimization of soil copper （Cu） could lay solid foundations for environmetal quality survey of agricultural soils at county scale. In this investigation, cokriging method was used to conduct the interpolation of Cu concentraiton in cropland soil in Shuangliu County, Sichuan Province, China. Based on the original 623 physicochmically measured soil samples, 560, 498, and 432 sub-samples were randomly selected as target variable and soil organic matter （SOM） of the whole original samples as auxiliary variable. Interpolation results using Cokriging under different sampling numbers were evaluated for their applicability in estimating the spatial distribution of soil Cu at county sacle. The results showed that the root mean square error （RMSE） produced by Cokriging decreased from 0.9 to 7.77%, correlation coefficient between the predicted values and the measured increased from 1.76 to 9.76% in comparison with the ordinary Kriging under the corresponding sample sizes. The prediction accuracy using Cokriging was still higher than original 623 data using ordinary Kriging even as sample size reduced 10%, and their interpolation maps were highly in agreement. Therefore, Cokriging was proven to be a more accurate and economic method which could provide more information and benefit for the studies on spatial distribution of soil pollutants at county scale.
基金supported by the National Natural Science Foundation of China (52371007 and 52301042)the National Key R&D Program of China (2020YFB0704503)+1 种基金the Guangdong Basic and Applied Basic Research Foundation (2021B1515120071)the Key-Area Research and Development Program of Guangdong Province (2023B0909050001)。
文摘Machine learning (ML) has been widely used todesign and develop new materials owing to its low computational cost and powerful predictive capabilities. In recentyears, the shortcomings of ML in materials science have gradually emerged, with a primary concern being the scarcity ofdata. It is challenging to build reliable and accurate ML modelsusing limited data. Moreover, the small sample size problemwill remain long-standing in materials science because of theslow accumulation of material data. Therefore, it is importantto review and categorize strategies for small-sample learningfor the development of ML in materials science. This reviewsystematically sorts the research progress of small-samplelearning strategies in materials science, including ensemblelearning, unsupervised learning, active learning, and transferlearning. The directions for future research are proposed, including few-shot learning, and virtual sample generation.More importantly, we emphasize the significance of embedding material domain knowledge into ML and elaborate on thebasic idea for implementing this strategy.
基金supported by the National Natural Science Foundation of China(Grant Nos.62471024 and 62301183)the Open Research Fund of Hanjiang Laboratory(KF2024001).
文摘Surface/underwater target classification is a key topic in marine information research.However,the complex underwater environment,coupled with the diversity of target types and their variable characteristics,presents significant challenges for classifier design.For shallow-water waveguides with a negative thermocline,a residual neural network(ResNet)model based on the sound field elevation structure is constructed.This model demonstrates robust classification performance even when facing low signal-to-noise ratios and environmental mismatches.Meanwhile,to address the reduced generalization ability caused by limited labeled acoustic data,an improved ResNet model based on unsupervised domain adaptation(“proposed UDA-ResNet”)is further constructed.This model incorporates data on simulated elevation structures of the sound field to augment the training process.Adversarial training is employed to extract domain-invariant features from simulated and trial data.These strategies help reduce the negative impact caused by domain differences.Experimental results demonstrate that the proposed method shows strong surface/underwater target classification ability under limited sample sizes,thus confirming its feasibility and effectiveness.
基金This paper was supported by the National Natural Science Foundation of China(Grant No.61972261)the Natural Science Foundation of Guangdong Province(No.2023A1515011667)+1 种基金the Key Basic Research Foundation of Shenzhen(No.JCYJ20220818100205012)the Basic Research Foundation of Shenzhen(No.JCYJ20210324093609026)。
文摘Random sample partition(RSP)is a newly developed big data representation and management model to deal with big data approximate computation problems.Academic research and practical applications have confirmed that RSP is an efficient solution for big data processing and analysis.However,a challenge for implementing RSP is determining an appropriate sample size for RSP data blocks.While a large sample size increases the burden of big data computation,a small size will lead to insufficient distribution information for RSP data blocks.To address this problem,this paper presents a novel density estimation-based method(DEM)to determine the optimal sample size for RSP data blocks.First,a theoretical sample size is calculated based on the multivariate Dvoretzky-Kiefer-Wolfowitz(DKW)inequality by using the fixed-point iteration(FPI)method.Second,a practical sample size is determined by minimizing the validation error of a kernel density estimator(KDE)constructed on RSP data blocks for an increasing sample size.Finally,a series of persuasive experiments are conducted to validate the feasibility,rationality,and effectiveness of DEM.Experimental results show that(1)the iteration function of the FPI method is convergent for calculating the theoretical sample size from the multivariate DKW inequality;(2)the KDE constructed on RSP data blocks with sample size determined by DEM can yield a good approximation of the probability density function(p.d.f);and(3)DEM provides more accurate sample sizes than the existing sample size determination methods from the perspective of p.d.f.estimation.This demonstrates that DEM is a viable approach to deal with the sample size determination problem for big data RSP implementation.
基金supported by the Fundamental Research Funds of the Chinese Academy of Forestry(CAFYBB2020QB004)the National Natural Science Foundation of China(41971038,32171559,U20A2085,and U21A2005).
文摘The sap flow method is widely used to estimate forest transpiration.However,at the individual tree level it has spatiotemporal variations due to the impacts of environmental conditions and spatial relationships among trees.Therefore,an in-depth understanding of the coupling effects of these factors is important for designing sap flow measurement methods and performing accurate assessments of stand scale transpiration.This study is based on observations of sap flux density(SF_(d))of nine sample trees with different Hegyi’s competition indices(HCIs),soil moisture,and meteorological conditions in a pure plantation of Larix gmelinii var.principis-rupprechtii during the 2021 growing season(May to September).A multifactorial model of sap flow was developed and possible errors in the stand scale sap flow estimates associated with sample sizes were determined using model-based predictions of sap flow.Temporal variations are controlled by vapour pressure deficit(VPD),solar radiation(R),and soil moisture,and these relationships can be described by polynomial or saturated exponential functions.Spatial(individual)differences were influenced by the HCI,as shown by the decaying power function.A simple SF_(d)model at the individual tree level was developed to describe the synergistic influences of VPD,R,soil moisture,and HCI.The coefficient of variations(CV)of the sap flow estimates gradually stabilized when the sample size was>10;at least six sample trees were needed if the CV was within 10%.This study improves understanding of the mechanisms of spatiotemporal variations in sap flow at the individual tree level and provides a new methodology for determining the optimal sample size for sap flow measurements.
基金funded by Gorgan University of Agricultural Sciences and Natural Resources(grant number 9318124503).
文摘Plant species diversity is one of the most widely used indicators in ecosystem management.The relation of species diversity with the size of the sample plot has not been fully determined for Oriental beech forests(Fagus orientalis Lipsky),a widespread species in the Hyrcanian region.Assessing the impacts of plot size on species diversity is fundamental for an ecosystem-based approach to forest management.This study determined the relation of species diversity and plot size by investigating species richness and abundance of both canopy and forest floor.Two hundred and fifty-six sample plots of 625 m^(2) each were layout in a grid pattern across 16 ha.Base plots(25 m×25 m)were integrated in different scales to investigate the effect of plot size on species diversity.The total included nine plots of 0.063,0.125,0.188,0.250,0.375,0.500,0.563,0.750 and 1 ha.Ten biodiversity indices were calculated.The results show that species richness in the different plot sizes was less than the actual value.The estimated value of the Simpson species diversity index was not significantly different from actual values for both canopy and forest floor diversity.The coefficient of variation of this index for the 1-ha sample plot showed the lowest amount across different plot sizes.Inverse Hill species diversity was insignificant difference across different plot sizes with an area greater than 0.500 ha.The modified Hill evenness index for the 1-ha sample size was a correct estimation of the 16-ha for both canopy and forest floor;however,the precision estimation was higher for the canopy layer.All plots greater than 0.250-ha provided an accurate estimation of the Camargo evenness index for forest floor species,but was inaccurate across different plot sizes for the canopy layer.The results indicate that the same plot size did not have the same effect across species diversity measurements.Our results show that correct estimation of species diversity measurements is related to the selection of appropriate indicators and plot size to increase the accuracy of the estimate so that the cost and time of biodiversity management may be reduced.
基金funding from the Royal Commission for the Exhibition of 1851provided as part of grant EP/1006761/1 from the Engineering and Physical Sciences Research Council
文摘This paper shows that for DEM simulations of triaxial tests using samples with a grading that is repre- sentative of a real soil, the sample size significantly influences the observed material response. Four DEM samples with identical initial states were produced： three cylindrical samples bounded by rigid wails and one bounded by a cubical periodic cell, When subjected to triaxial loading, the samples with rigid boundaries were more dilative, stiffer and reached a higher peak stress ratio than the sample enclosed by periodic boundaries. For the rigid-wall samples, dilatancy increased and stiffness decreased with increasing sample size, The periodic sample was effectively homogeneous, The void ratio increased and the contact density decreased close to the rigid walls, This heterogeneity reduced with increasing sample size. The positions of the critical state lines （CSLs） of the overall response in e-log p＇ space were sensitive to the sample size, although no difference was observed between their slopes. The critical states of the interior regions of the rigid-wall-bounded samples approached that of the homogeneous periodic sample with increasing sample size. The ultimate strength of the material at the critical state is independent of sample size.
