Whole lesion histogram analysis of apparent diffusion coefficient predicts therapy response in locally advanced rectal cancer

BACKGROUND Whole-tumor apparent diffusion coefficient(ADC)histogram analysis is relevant to predicting the neoadjuvant chemoradiation therapy(nCRT)response in patients with locally advanced rectal cancer(LARC).AIM To evaluate the performance of ADC histogram-derived parameters for predicting the outcomes of patients with LARC.METHODS This is a single-center,retrospective study,which included 48 patients with LARC.All patients underwent a pre-treatment magnetic resonance imaging(MRI)scan for primary tumor staging and a second restaging MRI for response evaluation.The sample was distributed as follows:18 responder patients(R)and 30 non-responders(non-R).Eight parameters derived from the whole-lesion histogram analysis(ADCmean,skewness,kurtosis,and ADC10^(th),25^(th),50^(th),75^(th),90^(th) percentiles),as well as the ADCmean from the hot spot region of interest(ROI),were calculated for each patient before and after treatment.Then all data were compared between R and non-R using the Mann-Whitney U test.Two measures of diagnostic accuracy were applied:the receiver operating characteristic curve and the diagnostic odds ratio(DOR).We also reported intra-and interobserver variability by calculating the intraclass correlation coefficient(ICC).RESULTS Post-nCRT kurtosis,as well as post-nCRT skewness,were significantly lower in R than in non-R(both P<0.001,respectively).We also found that,after treatment,R had a larger loss of both kurtosis and skewness than non-R(Δ%kurtosis and Δ skewness,P<0.001).Other parameters that demonstrated changes between groups were post-nCRT ADC10^(th),Δ%ADC10^(th),Δ%ADCmean,and ROIΔ%ADCmean.However,the best diagnostic performance was achieved byΔ%kurtosis at a threshold of 11.85%(Area under the receiver operating characteristic curve[AUC]=0.991,DOR=376),followed by post-nCRT kurtosis=0.78×10^(-3)mm^(2)/s(AUC=0.985,DOR=375.3),Δskewness=0.16(AUC=0.885,DOR=192.2)and post-nCRT skewness=1.59×10^(-3)mm^(2)/s(AUC=0.815,DOR=168.6).Finally,intraclass correlation coefficient analysis showed excellent intraobserver and interobserver agreement,ensuring the implementation of histogram analysis into routine clinical practice.CONCLUSION Whole-tumor ADC histogram parameters,particularly kurtosis and skewness,are relevant biomarkers for predicting the nCRT response in LARC.Both parameters appear to be more reliable than ADCmean from one-slice ROI.

Partial Time-Varying Coefficient Regression and Autoregressive Mixed Model

Regression and autoregressive mixed models are classical models used to analyze the relationship between time series response variable and other covariates. The coefficients in traditional regression and autoregressive mixed models are constants. However, for complicated data, the coefficients of covariates may change with time. In this article, we propose a kind of partial time-varying coefficient regression and autoregressive mixed model and obtain the local weighted least-square estimators of coefficient functions by the local polynomial technique. The asymptotic normality properties of estimators are derived under regularity conditions, and simulation studies are conducted to empirically examine the finite-sample performances of the proposed estimators. Finally, we use real data about Lake Shasta inflow to illustrate the application of the proposed model.

Partial Time-Varying Coefficient Regression and Autoregressive Mixed Model

Regression and autoregressive mixed models are classical models used to analyze the relationship between time series response variable and other covariates. The coefficients in traditional regression and autoregressive mixed models are constants. However, for complicated data, the coefficients of covariates may change with time. In this article, we propose a kind of partial time-varying coefficient regression and autoregressive mixed model and obtain the local weighted least-square estimators of coefficient functions by the local polynomial technique. The asymptotic normality properties of estimators are derived under regularity conditions, and simulation studies are conducted to empirically examine the finite-sample performances of the proposed estimators. Finally, we use real data about Lake Shasta inflow to illustrate the application of the proposed model.

Improved calibration method for displacement transformation coefficient in optical and visual measurements

Optical and visual measurement technology is used widely in fields that involve geometric measurements,and among such technology are laser and vision-based displacement measuring modules(LVDMMs).The displacement transformation coefficient(DTC)of an LVDMM changes with the coordinates in the camera image coordinate system during the displacement measuring process,and these changes affect the displacement measurement accuracy of LVDMMs in the full field of view(FFOV).To give LVDMMs higher accuracy in the FFOV and make them adaptable to widely varying measurement demands,a new calibration method is proposed to improve the displacement measurement accuracy of LVDMMs in the FFOV.First,an image coordinate system,a pixel measurement coordinate system,and a displacement measurement coordinate system are established on the laser receiving screen of the LVDMM.In addition,marker spots in the FFOV are selected,and the DTCs at the marker spots are obtained from calibration experiments.Also,a fitting method based on locally weighted scatterplot smoothing(LOWESS)is selected,and with this fitting method the distribution functions of the DTCs in the FFOV are obtained based on the DTCs at the marker spots.Finally,the calibrated distribution functions of the DTCs are applied to the LVDMM,and experiments conducted to verify the displacement measurement accuracies are reported.The results show that the FFOV measurement accuracies for horizontal and vertical displacements are better than±15μm and±19μm,respectively,and that for oblique displacement is better than±24μm.Compared with the traditional calibration method,the displacement measurement error in the FFOV is now 90%smaller.This research on an improved calibration method has certain significance for improving the measurement accuracy of LVDMMs in the FFOV,and it provides a new method and idea for other vision-based fields in which camera parameters must be calibrated.

ASSESSMENT OF LOCAL INFLUENCE FOR GENERALIZED CORRELATION COEFFICIENTS

In this paper, we study local influence analysis for Zhang's generalized correlation coefficients and Hotelling's generalized correlation coefficient by using approach. of local influence analysis suggested by Shi (1991), i.e., generalized influence function (GIF) and generalized Cook distance (GCD). An example is given to illustrate our results.

The Study on Pipe Sudden Enlargem entLocal Resistant Coefficient

During the design of pipeline,the determination of local resistant coefficient is often come arcoss.The sudden enlargement local resistant coefficient ξ 1=1-A 1A 2 2 is determined through theory.In the paper,the sudden enlargement local resistant coefficient under the conditions of three kinds of A 1A 2 was studied in experiment.In the end ,the result shows that ξ 1 is related not only to two flow cross sections,but also to the velocity.Through experimental research,the relationship between ξ 1,A 1A 2 and V 1 was determined.In a word,the hydraulic calculation of pipeline can be done by taking correspondent ξ 1 ,according to the design velocity V 1 and A 1A 2.

Experimental Determination of Local Resistance Coefficient of Sudden Expansion Tube

Theoretical derivation of local resistance coefficient of sudden expansion tube is presented. Several assumptions are analyzed in the theoretical derivation. That the head loss shall be neglected is affirmed. Experimental data proves that the pressure before and after sudden expansion section is basically the same. That the friction force on the side face of control body is neglected is denied and it is pointed out that such neglect is the main cause for error between theoretical calculation and actual measurement. Experimental device for measuring local resistance coefficient is designed in combination with theoretical derivation process. Optimal gradually varied flow section is selected after sudden expansion pipe in Bernoulli equation based on variation of piezometer tube head. It is pointed out in accordance with experimental data analysis that the value of local resistance coefficient of sudden expansion tube determined through experimental data is closer to the actual situation during pipeline design.

Local Empirical Likelihood Diagnosis of Varying Coefficient Density-Ratio Models Based on Case-Control Data

In this paper, a varying-coefficient density-ratio model for case-control studies is developed. We investigate the local empirical likelihood diagnosis of varying coefficient density-ratio model for case-control data. The local empirical log-likelihood ratios for the nonparametric coefficient functions are introduced. First, the estimation equations based on empirical likelihood method are established. Then, a few of diagnostic statistics are proposed. At last, we also examine the performance of proposed method for finite sample sizes through simulation studies.

A Correlation Coefficient Approach for Evaluation of Stiffness Degradation of Beams Under Moving Load

This paper presents a new approach using correlation and cross-correlation coefficients to evaluate the stiffness degradation of beams under moving load.The theoretical study of identifying defects by vibration methods showed that the traditional methods derived from the vibration measurement data have not met the needs of the actual issues.We show that the correlation coefficients allow us to evaluate the degree and the effectiveness of the defects on beams.At the same time,the cross-correlation model is the basis for determining the relative position of defects.The results of this study are experimentally conducted to confirm the relationship between the correlation coefficients and the existence of the defects.In particular,the manuscript shows that the sensitivity of the correlation coefficients and cross-correlation is much higher than the parameters such as changes in stiffness(EJ)and natural frequency values(Δf).This study suggests using the above parameters to evaluate the stiffness degradation of beams by vibration measurement data in practice.

FUNCTIONAL-COEFFICIENT REGRESSION MODEL AND ITS ESTIMATION

In this paper,a class of functional-coefficient regression models is proposed and an estimation procedure based on the locally weighted least equares is suggested.This class of models,with the proposed estimation method,is a powerful means for exploratory data analysis.

Effects of signal modulation and coloured cross-correlation of coloured noises on the diffusion of a harmonic oscillator

The diffusion in a harmonic oscillator driven by coloured noises ξ（t） and η（t） with coloured cross-correlation in which one of the noises is modulated by a biased periodic signal is investigated. The exact expression of diffusion coefficient d as a function of noise parameter, signal parameter, and oscillator frequency is derived. The findings in this paper are as follows. 1） The curves of d versus noise intensity D and d versus noises cross-correlation time z3 exist as two different phases. The transition between the two phases arises from the change of the cross-correlation coefficient A of the two Ornstein-Uhlenbeck （O-U） noises. 2） Changing the value of T3, the curves of d versus Q, the intensity of colored noise that is modulated by the signal, can transform from a phase having a minimum to a monotonic phase. 3） Changing the value of signal amplitude A, d versus Q curves can transform from a phase having a minimum to a monotonic phase. The above-mentioned results demonstrate that a like noise-induced transition appears in the model.

DIFFERENCE SCHEMES BASING ON COEFFICIENT APPROXIMATION

In respect of variable coefficient differential equations, the equations of coefficient function approximation were more accurate than the coefficient to be frozen as a constant in every discrete subinterval. Usually, the difference schemes constructed based on Taylor expansion approximation of the solution do not suit the solution with sharp function. Introducing into local bases to be combined with coefficient function approximation, the difference can well depict more complex physical phenomena, for example, boundary layer as well as high oscillatory,with sharp behavior. The numerical test shows the method is more effective than the traditional one.

ADDITIVE HAZARDS MODEL WITH TIME-VARYING REGRESSION COEFFICIENTS

This article discusses regression analysis of failure time under the additive hazards model, when the regression coefficients are time-varying. The regression coefficients are estimated locally based on the pseudo-score function [12] in a window around each time point. The proposed method can be easily implemented, and the resulting estimators are shown to be consistent and asymptotically normal with easily estimated variances. The simulation studies show that our estimation procedure is reliable and useful.

EFFICIENT ESTIMATION OF FUNCTIONAL-COEFFICIENT REGRESSION MODELS WITH DIFFERENT SMOOTHING VARIABLES

In this article,a procedure for estimating the coefficient functions on the functional-coefficient regression models with different smoothing variables in different coefficient functions is defined.First step,by the local linear technique and the averaged method,the initial estimates of the coefficient functions are given.Second step,based on the initial estimates,the efficient estimates of the coefficient functions are proposed by a one-step back-fitting procedure.The efficient estimators share the same asymptotic normalities as the local linear estimators for the functional-coefficient models with a single smoothing variable in different functions.Two simulated examples show that the procedure is effective.

The Latest Progress in Varying-coefficient Models

变化系数模型是古典线性模型的有用延期。他们广泛地被用于经济， biomedicine，传染病学等等。他们上有广泛的研究在最近三十年年。在这份报纸，许多与变化系数模型有关的模型被聚集起来。各种变化系数模型上的假设测试的评价过程和理论被总结。从我的意见，等待学习的一些方面被建议。

Generalized Likelihood Ratio Tests for Varying-Coefficient Models with Censored Data

In this paper, we extend the generalized likelihood ratio test to the varying-coefficient models with censored data. We investigate the asymptotic behavior of the proposed test and demonstrate that its limiting null distribution follows a distribution, with the scale constant and the number of degree of freedom being independent of nuisance parameters or functions, which is called the wilks phenomenon. Both simulated and real data examples are given to illustrate the performance of the testing approach.

Non-contact of Solutions to Stochastic Differential Equations Driven by Semimartingale with Non-Lipschitz Coefficients

A class of stochastic differential equations(SDEs) driven by semimartingale with non-Lipschitz coefficients was studied.By using Gronwall inequality,the non-confluence of solutions is proved under the general conditions.

基于反射系数谱的配电电缆局部缺陷识别定位

传统配电电缆在局部缺陷识别与精准定位上灵敏度较差,位置范围识别受到限制,为解决现有技术在配电电缆缺陷诊断上存在的不足,提出一种基于反射系数谱的配电电缆局部缺陷识别定位方法。首先依据电缆分布参数模型,获得配电电缆完好状态与存在局部缺陷段的反射系数谱,然后利用广义正交积分法,将反射系数谱的虚部从频域转换到空间域,建立积分诊断图,得到具有直观性的定位图谱,根据积分诊断图实现配电电缆局部缺陷的识别与精准定位,方法适用于同时存在多处电缆缺陷的情况。最后,在实验室50 m长的配电电缆上制作老化与破损两种缺陷,用于验证所提方法的有效性。仿真和实验结果表明,该方法对不同缺陷情况均具有较高的识别精度,定位误差小于0.15 m。

基于深度神经网络的多聚焦红外图像非线性增强

当红外图像中含有多个聚焦目标主体时,会导致红外图像质量下降,部分区域出现模糊,因此,提出基于深度神经网络的多聚焦红外图像非线性增强方法。在引导滤波的作用下,从红外图像中获取细节层图像和背景层图像,在细节层图像中建立局部清晰度评价函数,得到清晰的细节层和背景层并融合二者。利用构建的深度神经网络结构,建立非线性增益函数,通过设定阈值和调整子带系数,实现对多聚焦红外图像的非线性增强。测试结果表明,所提方法在增强图像过程中,并没有改变原始图像的亮度和纹理波动;增强后的图像信息熵比原图像提高了57%左右,图像抗噪性能值更高,平均为7.4 dB,图像更清晰,SSIM值更趋近于1,平均为0.98,增强后的图片与原图片图像相似度更高,更接近于真实图像。

地方高校高质量发展水平测度、区域差异及分布动态演进

在构建地方高校高质量发展评价指标体系的基础上,利用全国31个省份的2004—2021年面板数据,使用熵权TOPSIS法测度地方高校高质量发展水平并分析我国地方高校高质量发展的时空特征、区域差异以及分布动态演进,研究结果表明:地方高校高质量发展水平整体不高但呈波动上升趋势;我国区域地方高校高质量发展不平衡,呈现东部-东北部-中部-西部依次递减态势;地方高校高质量发展水平存在显著的区域差异,主要来源于区域间差异,但有缩小的趋势,且西部和东北地区伴有极化情况出现。