As for CaZrO_(3)(CZ)ceramic,the reported dielectric property values,especially dielectric constants,were much different from 23 to 32,which is reliable and credible?Without precise property data,CZ can’t be further d...As for CaZrO_(3)(CZ)ceramic,the reported dielectric property values,especially dielectric constants,were much different from 23 to 32,which is reliable and credible?Without precise property data,CZ can’t be further developed and utilized accurately.Herein,CZ ceramic was fabricated by a traditional two-step sintering process,then simulated and calculated the dielectric properties precisely at a microscopic polarization angle using the lattice vibrational spectra and the Clausius-Mossotti(C-M)as well as damping equations.The Raman and Fourier transform far-infrared modes were analyzed and used to predict the intrinsic properties,which were consistent well with the values calculated from C-M and damping equations.The intrinsic permittivity,after precise prediction,is about 20,which is reliable and credible.As for the dielectric loss,the value of about 6×10^(-4)was obtained after precise calculation,which is similar to other results.展开更多
In this editorial,we comment on the article by Zhang et al entitled Development of a machine learning-based model for predicting the risk of early postoperative recurrence of hepatocellular carcinoma.Hepatocellular ca...In this editorial,we comment on the article by Zhang et al entitled Development of a machine learning-based model for predicting the risk of early postoperative recurrence of hepatocellular carcinoma.Hepatocellular carcinoma(HCC),which is characterized by high incidence and mortality rates,remains a major global health challenge primarily due to the critical issue of postoperative recurrence.Early recurrence,defined as recurrence that occurs within 2 years posttreatment,is linked to the hidden spread of the primary tumor and significantly impacts patient survival.Traditional predictive factors,including both patient-and treatment-related factors,have limited predictive ability with respect to HCC recurrence.The integration of machine learning algorithms is fueled by the exponential growth of computational power and has revolutionized HCC research.The study by Zhang et al demonstrated the use of a groundbreaking preoperative prediction model for early postoperative HCC recurrence.Challenges persist,including sample size constraints,issues with handling data,and the need for further validation and interpretability.This study emphasizes the need for collaborative efforts,multicenter studies and comparative analyses to validate and refine the model.Overcoming these challenges and exploring innovative approaches,such as multi-omics integration,will enhance personalized oncology care.This study marks a significant stride toward precise,efficient,and personalized oncology practices,thus offering hope for improved patient outcomes in the field of HCC treatment.展开更多
The spatial estimation for soil properties was improved and sampling intensities also decreased in terms of incorporated auxiliary data. In this study, kriging and two interpolation methods were proven well to estimat...The spatial estimation for soil properties was improved and sampling intensities also decreased in terms of incorporated auxiliary data. In this study, kriging and two interpolation methods were proven well to estimate auxiliary variables： cokriging and regression-kriging, and using the salinity data from the first two stages as auxiliary variables, the methods both improved the interpolation of soil salinity in coastal saline land. The prediction accuracy of the three methods was observed under different sampling density of the target variable by comparison with another group of 80 validation sample points, from which the root-mean-square error （RMSE） and correlation coefficient （r） between the predicted and measured values were calculated. The results showed, with the help of auxiliary data, whatever the sample size of the target variable may be, cokriging and regression-kriging performed better than ordinary kriging. Moreover, regression-kriging produced on average more accurate predictions than cokriging. Compared with the kriging results, cokriging improved the estimations by reducing RMSE from 23.3 to 29% and increasing r from 16.6 to 25.5%, regression-kriging improved the estimations by reducing RMSE from 25 to 41.5% and increasing r from 16.8 to 27.2%. Therefore, regression-kriging shows promise for improved prediction for soil salinity and reduction of soil sampling intensity considerably while maintaining high prediction accuracy. Moreover, in regression-kriging, the regression model can have any form, such as generalized linear models, non-linear models or tree-based models, which provide a possibility to include more ancillary variables.展开更多
Based on the review and comparison of main statistical analysis models for estimating variety-environment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predi...Based on the review and comparison of main statistical analysis models for estimating variety-environment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predictive precision of these models were compared by cross validation of an example data. Results showed that the order of model precision was LR-PCA model > AMMI model > PCA model > Treatment Means (TM) model > Linear Regression (LR) model > Additive Main Effects ANOVA model. The precision gain factor of LR-PCA model was 1.55, increasing by 8.4% compared with AMMI.展开更多
In order to satisfy the demand of validity and real time operating performance of diesel engine model used in hardware-in-the-loop simulation system,a simplified quasi-dimensional model for diesel engine working proce...In order to satisfy the demand of validity and real time operating performance of diesel engine model used in hardware-in-the-loop simulation system,a simplified quasi-dimensional model for diesel engine working process was proposed,which was based on the phase-divided spray mixing model.The software MATLAB/Simulink was utilized to simulate diesel engine performance parameters.The comparisons between calculated results and experimental data show that the relative error of power and brake specific fuel consumption is less than 2.8%,and the relative error of nitric oxide and soot emissions is less than 9.1%.At the same time,the average computational time for simulation of one working process with the new model is 36 s,which presents good real time operating performance of the model.The simulation results also indicate that the nozzle flow coefficient has great influence on the prediction precision of performance parameters in diesel engine simulation model.展开更多
Rarefaction effect appears when gas flows in micro/nano channels,so it is difficult to accurately predict real gas flow rate by using the classical theory.It is necessary to establish a more accurate and universal per...Rarefaction effect appears when gas flows in micro/nano channels,so it is difficult to accurately predict real gas flow rate by using the classical theory.It is necessary to establish a more accurate and universal permeability correction model to describe the flow behavior of rarefied gas.In this work,the gas flow in a plate micro-scale channel was numerically simulated using R26 moment method,and the simulation results were compared with those of the direct simulation Monte Carlo method(DSMC method)and R13 moment method.Then,a gas permeability correction model for plate micro-scale channels and circular micro-scale channels was established based on the simulation results of the R26 moment method,and used to describe the flow behavior of rarefied gas in micro-scale channels.Finally,the gas permeability correction co-efficient for different Knudsen numbers was calculated and compared with the prediction results of the Tang model,the available experimental data and the solution of linearized Boltzmann equation.The following research results were obtained.First,when the R26 moment method is used to describe the rarefaction effect of gas,its result is accordant with the calculation result of the DSMC method,and its calculation accuracy is higher than that of R13 moment method.Second,the gas permeability correction coefficient which is calculated by using the higher-order Knudsen's gas permeability correction model for plate micro-scale channels is in accordance with the experimental data and the solution of linearized Boltzmann equation.Third,the gas permeability correction coefficient which is calculated by using the higher-order Knudsen's gas permeability correction model for circular micro-scale channels is accordant with the solution of linearized Boltzmann equation.In conclusion,this higher-order Knudsen's gas permeability correction model is advantageous with high prediction precision and universality,and it can be used to describe the rarefaction effect of gas in micro/nano-scale channels.展开更多
Precise determination of the Higgs boson self-couplings is essential for understanding the mechanism underlying electroweak symmetry breaking.However,owing to the limited number of Higgs boson pair events at the LHC,o...Precise determination of the Higgs boson self-couplings is essential for understanding the mechanism underlying electroweak symmetry breaking.However,owing to the limited number of Higgs boson pair events at the LHC,only loose constraints have been established to date.Current constraints are based on the assumption that the cross section is a quadratic function of the trilinear Higgs self-coupling within the framework.Incorporating higher-order quantum corrections from virtual Higgs bosons would significantly alter this functional form,introducing new quartic and cubic power dependencies on the trilinear Higgs self-coupling.To derive this new functional form,we propose a specialized renormalization procedure that tracks all Higgs self-couplings at each calculation step.Additionally,we introduce renormalization constants for coupling modifiers within the framework to ensure the cancellation of all ultraviolet divergences.With new functional forms of the cross sections in both the gluon-gluon fusion and vector boson fusion channels,the upper limit of kλ_(3H)=λ_(3H)^(SM)set by the ATLAS(CMS)collaboration is reduced from 6.6(6.49)to 5.4(5.37).However,extracting a meaningful constraint on the quartic Higgs self-coupling from Higgs boson pair production data remains challenging.We also present the invariant mass distributions of the Higgs boson pair at different values of the self-couplings,which could assist in setting optimal cuts for experimental analysis.展开更多
The common models used for grey system predictions include the GM(1, 1), the GM(1, N),the GM(N, 1), and so on, but their whitening equations are all single ordinary differential equations.However, objects and factors ...The common models used for grey system predictions include the GM(1, 1), the GM(1, N),the GM(N, 1), and so on, but their whitening equations are all single ordinary differential equations.However, objects and factors generally form a whole through mutual restrictions and connections when the objective world is developing and changing continuously. In other words, variables affect each other. The relationship can’t be properly reflected by the single differential equation. Therefore, the paper proposes a novel simultaneous grey model. The paper gives a modeling method of simultaneous grey model SGM(1, 2) with 2 interactive variables. The example proves that the simultaneous grey model has high precision and improves the precision significantly compared with the conventional single grey model. The new method proposed enriches the grey modeling method system and has important significance for the in-depth study, popularization and application of grey models.展开更多
基金the National Natural Science Foundation of China(51641206)Scientific Research Foundation of Shandong University of Science and Technology for Recruited Talents(Grant No.2016RCJJ002)the Opening Project of State Key Laboratory of High Performance Ceramics and Superfine Microstructure(Grant No.SKL201503SIC).
文摘As for CaZrO_(3)(CZ)ceramic,the reported dielectric property values,especially dielectric constants,were much different from 23 to 32,which is reliable and credible?Without precise property data,CZ can’t be further developed and utilized accurately.Herein,CZ ceramic was fabricated by a traditional two-step sintering process,then simulated and calculated the dielectric properties precisely at a microscopic polarization angle using the lattice vibrational spectra and the Clausius-Mossotti(C-M)as well as damping equations.The Raman and Fourier transform far-infrared modes were analyzed and used to predict the intrinsic properties,which were consistent well with the values calculated from C-M and damping equations.The intrinsic permittivity,after precise prediction,is about 20,which is reliable and credible.As for the dielectric loss,the value of about 6×10^(-4)was obtained after precise calculation,which is similar to other results.
文摘In this editorial,we comment on the article by Zhang et al entitled Development of a machine learning-based model for predicting the risk of early postoperative recurrence of hepatocellular carcinoma.Hepatocellular carcinoma(HCC),which is characterized by high incidence and mortality rates,remains a major global health challenge primarily due to the critical issue of postoperative recurrence.Early recurrence,defined as recurrence that occurs within 2 years posttreatment,is linked to the hidden spread of the primary tumor and significantly impacts patient survival.Traditional predictive factors,including both patient-and treatment-related factors,have limited predictive ability with respect to HCC recurrence.The integration of machine learning algorithms is fueled by the exponential growth of computational power and has revolutionized HCC research.The study by Zhang et al demonstrated the use of a groundbreaking preoperative prediction model for early postoperative HCC recurrence.Challenges persist,including sample size constraints,issues with handling data,and the need for further validation and interpretability.This study emphasizes the need for collaborative efforts,multicenter studies and comparative analyses to validate and refine the model.Overcoming these challenges and exploring innovative approaches,such as multi-omics integration,will enhance personalized oncology care.This study marks a significant stride toward precise,efficient,and personalized oncology practices,thus offering hope for improved patient outcomes in the field of HCC treatment.
基金the National Natural Science Foundation of China （40571066, 40001008）the Postdoctoral Science Foundation of China （20060401048） the Key Program of Science and Technology Bureau of Zhejiang Province, China 030523）.
文摘The spatial estimation for soil properties was improved and sampling intensities also decreased in terms of incorporated auxiliary data. In this study, kriging and two interpolation methods were proven well to estimate auxiliary variables： cokriging and regression-kriging, and using the salinity data from the first two stages as auxiliary variables, the methods both improved the interpolation of soil salinity in coastal saline land. The prediction accuracy of the three methods was observed under different sampling density of the target variable by comparison with another group of 80 validation sample points, from which the root-mean-square error （RMSE） and correlation coefficient （r） between the predicted and measured values were calculated. The results showed, with the help of auxiliary data, whatever the sample size of the target variable may be, cokriging and regression-kriging performed better than ordinary kriging. Moreover, regression-kriging produced on average more accurate predictions than cokriging. Compared with the kriging results, cokriging improved the estimations by reducing RMSE from 23.3 to 29% and increasing r from 16.6 to 25.5%, regression-kriging improved the estimations by reducing RMSE from 25 to 41.5% and increasing r from 16.8 to 27.2%. Therefore, regression-kriging shows promise for improved prediction for soil salinity and reduction of soil sampling intensity considerably while maintaining high prediction accuracy. Moreover, in regression-kriging, the regression model can have any form, such as generalized linear models, non-linear models or tree-based models, which provide a possibility to include more ancillary variables.
文摘Based on the review and comparison of main statistical analysis models for estimating variety-environment cell means in regional crop trials, a new statistical model, LR-PCA composite model was proposed, and the predictive precision of these models were compared by cross validation of an example data. Results showed that the order of model precision was LR-PCA model > AMMI model > PCA model > Treatment Means (TM) model > Linear Regression (LR) model > Additive Main Effects ANOVA model. The precision gain factor of LR-PCA model was 1.55, increasing by 8.4% compared with AMMI.
基金Project(2006A10GX059) supported by the Science and Technology Plan of Dalian,China
文摘In order to satisfy the demand of validity and real time operating performance of diesel engine model used in hardware-in-the-loop simulation system,a simplified quasi-dimensional model for diesel engine working process was proposed,which was based on the phase-divided spray mixing model.The software MATLAB/Simulink was utilized to simulate diesel engine performance parameters.The comparisons between calculated results and experimental data show that the relative error of power and brake specific fuel consumption is less than 2.8%,and the relative error of nitric oxide and soot emissions is less than 9.1%.At the same time,the average computational time for simulation of one working process with the new model is 36 s,which presents good real time operating performance of the model.The simulation results also indicate that the nozzle flow coefficient has great influence on the prediction precision of performance parameters in diesel engine simulation model.
文摘Rarefaction effect appears when gas flows in micro/nano channels,so it is difficult to accurately predict real gas flow rate by using the classical theory.It is necessary to establish a more accurate and universal permeability correction model to describe the flow behavior of rarefied gas.In this work,the gas flow in a plate micro-scale channel was numerically simulated using R26 moment method,and the simulation results were compared with those of the direct simulation Monte Carlo method(DSMC method)and R13 moment method.Then,a gas permeability correction model for plate micro-scale channels and circular micro-scale channels was established based on the simulation results of the R26 moment method,and used to describe the flow behavior of rarefied gas in micro-scale channels.Finally,the gas permeability correction co-efficient for different Knudsen numbers was calculated and compared with the prediction results of the Tang model,the available experimental data and the solution of linearized Boltzmann equation.The following research results were obtained.First,when the R26 moment method is used to describe the rarefaction effect of gas,its result is accordant with the calculation result of the DSMC method,and its calculation accuracy is higher than that of R13 moment method.Second,the gas permeability correction coefficient which is calculated by using the higher-order Knudsen's gas permeability correction model for plate micro-scale channels is in accordance with the experimental data and the solution of linearized Boltzmann equation.Third,the gas permeability correction coefficient which is calculated by using the higher-order Knudsen's gas permeability correction model for circular micro-scale channels is accordant with the solution of linearized Boltzmann equation.In conclusion,this higher-order Knudsen's gas permeability correction model is advantageous with high prediction precision and universality,and it can be used to describe the rarefaction effect of gas in micro/nano-scale channels.
基金Supported in part by the National Natural Science Foundation of China(12275156,12321005,12375076)and the Taishan Scholar Foundation of Shandong province(tsqn201909011)。
文摘Precise determination of the Higgs boson self-couplings is essential for understanding the mechanism underlying electroweak symmetry breaking.However,owing to the limited number of Higgs boson pair events at the LHC,only loose constraints have been established to date.Current constraints are based on the assumption that the cross section is a quadratic function of the trilinear Higgs self-coupling within the framework.Incorporating higher-order quantum corrections from virtual Higgs bosons would significantly alter this functional form,introducing new quartic and cubic power dependencies on the trilinear Higgs self-coupling.To derive this new functional form,we propose a specialized renormalization procedure that tracks all Higgs self-couplings at each calculation step.Additionally,we introduce renormalization constants for coupling modifiers within the framework to ensure the cancellation of all ultraviolet divergences.With new functional forms of the cross sections in both the gluon-gluon fusion and vector boson fusion channels,the upper limit of kλ_(3H)=λ_(3H)^(SM)set by the ATLAS(CMS)collaboration is reduced from 6.6(6.49)to 5.4(5.37).However,extracting a meaningful constraint on the quartic Higgs self-coupling from Higgs boson pair production data remains challenging.We also present the invariant mass distributions of the Higgs boson pair at different values of the self-couplings,which could assist in setting optimal cuts for experimental analysis.
基金Supported by the National Natural Science Foundation of China (11401418)。
文摘The common models used for grey system predictions include the GM(1, 1), the GM(1, N),the GM(N, 1), and so on, but their whitening equations are all single ordinary differential equations.However, objects and factors generally form a whole through mutual restrictions and connections when the objective world is developing and changing continuously. In other words, variables affect each other. The relationship can’t be properly reflected by the single differential equation. Therefore, the paper proposes a novel simultaneous grey model. The paper gives a modeling method of simultaneous grey model SGM(1, 2) with 2 interactive variables. The example proves that the simultaneous grey model has high precision and improves the precision significantly compared with the conventional single grey model. The new method proposed enriches the grey modeling method system and has important significance for the in-depth study, popularization and application of grey models.
