Adjuvant chemotherapy for isolated resectable colorectal lung metastasis: A retrospective study using inverse probability treatment weighting propensity analysis

BACKGROUND The benefit of adjuvant chemotherapy(ACT)for patients with no evidence of disease after pulmonary metastasis resection(PM)from colorectal cancer(CRC)remains controversial.AIM To assess the efficacy of ACT in patients after PM resection for CRC.METHODS This study included 96 patients who underwent pulmonary metastasectomy for CRC at a single institution between April 2008 and July 2023.The primary end-point was overall survival(OS);secondary endpoints included cancer-specific survival(CSS)and disease-free survival(DFS).An inverse probability of treat-ment-weighting(IPTW)analysis was conducted to address indication bias.Sur-vival outcomes compared using Kaplan-Meier curves,log-rank test,Cox regre-ssion and confirmed by propensity score-matching(PSM).RESULTS With a median follow-up of 27.5 months(range,18.3-50.4 months),the 5-year OS,CSS and DFS were 72.0%,74.4%and 51.3%,respectively.ACT had no significant effect on OS after PM resection from CRC[original cohort:P=0.08;IPTW:P=0.15].No differences were observed for CSS(P=0.12)and DFS(P=0.68)between the ACT and non-ACT groups.Multivariate analysis showed no association of ACT with better survival,while sublobar resection(HR=0.45;95%CI:0.20-1.00,P=0.049)and longer disease-free interval(HR=0.45;95%CI:0.20-0.98,P=0.044)were associated with improved survival.CONCLUSION ACT does not improve survival after PM resection for CRC.Further well-designed randomized controlled trials are needed to determine the optimal ACT regimen and duration.

A note on the Moore-Penrose inverse of a companion matrix

Let R be an associative ring with unity 1. The existence of the Moore-Penrose inverses of block matrices overR is investigated and the sufficient ad necessary conditions for such existence are obtained. Furthermore, the representation of the Moore-Penrose inverse of M=[0 A C B]is given under the condition of EBF - 0, where E - I - CCT and F - I -AfA. This result generalizes the representation of the Moore-Penrose inverse of the companion matrix M =[0 a In b]due to Pedro Patricio. As for applications, some examples are given to illustrate the obtained results.

A NEW PERTURBATION THEOREM FOR MOORE-PENROSE METRIC GENERALIZED INVERSE OF BOUNDED LINEAR OPERATORS IN BANACH SPACES

In this paper, we investigate a new perturbation theorem for the Moore-Penrose metric generalized inverses of a bounded linear operator in Banach space. The main tool in this paper is ＂the generalized Neumann lemma＂ which is quite different from the method in [12] where ＂the generalized Banach lemma＂ was used. By the method of the perturba- tion analysis of bounded linear operators, we obtain an explicit perturbation theorem and three inequalities about error estimates for the Moore-Penrose metric generalized inverse of bounded linear operator under the generalized Neumann lemma and the concept of stable perturbations in Banach spaces.

The Reverse Order Law for Moore-Penrose Inverse of Closed Operators

In this paper, the reverse order law for the Moore-Penrose inverse of closed linear operators with closed range is investigated by virtue of the Norm-preserving extension of the bounded linear operators. The results generalize some results obtained by S Izumino in [12].

Moore-Penrose Inverses and Group Inverses of Block k-Circulant Matrices

The Moore-Penrose inverse of a block k-circulant matrix whose blocks are arbitrary matrices are obtained when k has unit modulus. In the meantime. explicit formulae for finding group inverses of certain specified k-circulant matrices are also given.

Unified Approach to the Expression for the Moore-Penrose Inverse of a- xy

Let A be an unital C*-algebra, a, x and y are elements in A. In this paper, we present a method how to calculate the Moore-Penrose inverse of a- xy*and investigate the expression for some new special cases of(a- xy*).

Properties, Inference and Applications of Inverse Power Two-Parameter Weighted Lindley Distribution

We proposed “a new extension of three-parametric distribution” called the inverse power two-parameter weighted Lindley (IPWL) distribution capable of modeling a upside-down bathtub hazard rate function. This distribution is studied to get basic structural properties such as reliability measures, moments, inverse moments and its related measures. Simulation studies are done to present the performance and behavior of maximum likelihood estimates of the IPWL distribution parameters. Finally, we perform goodness of fit measures and test statistics using a real data set to show the performance of the new distribution.

Computing the Moore-Penrose Inverse of a Matrix Through Symmetric Rank-One Updates

This paper presents a recursive procedure to compute the Moore-Penrose inverse of a matrix A. The method is based on the expression for the Moore-Penrose inverse of rank-one modified matrix. The computational complexity of the method is analyzed and a numerical example is included. A variant of the algorithm with lower computational complexity is also proposed. Both algorithms are tested on randomly generated matrices. Numerical performance confirms our theoretic results.

RESEARCHES ON INVERSE ORDER RULE FOR WEIGHTED GENERALIZED INVERSE

The weighted generalized inverses have several important applications in researching the singular matrices,regularization methods for ill-posed problems, optimization problems and statis- tics problems.In this paper we further research inverse order rules of weighted generalizde inverse. From the view point of munerical algebra, the different methods we used in inverse order rules pro- vide beneficial means for theory and computing of generalized inverse matrices.

Perturbation Analysis for t-Product-Based Tensor Inverse,Moore-Penrose Inverse and Tensor System

This paper establishes some perturbation analysis for the tensor inverse,the tensor Moore-Penrose inverse,and the tensor system based on the t-product.In the settings of structured perturbations,we generalize the Sherman-Morrison-Woodbury(SMW)formula to the t-product tensor scenarios.The SMW formula can be used to perform the sensitivity analy-sis for a multilinear system of equations.

A Normal Weighted Inverse Gaussian Distribution for Skewed and Heavy-Tailed Data

High frequency financial data is characterized by non-normality: asymmetric, leptokurtic and fat-tailed behaviour. The normal distribution is therefore inadequate in capturing these characteristics. To this end, various flexible distributions have been proposed. It is well known that mixture distributions produce flexible models with good statistical and probabilistic properties. In this work, a finite mixture of two special cases of Generalized Inverse Gaussian distribution has been constructed. Using this finite mixture as a mixing distribution to the Normal Variance Mean Mixture we get a Normal Weighted Inverse Gaussian (NWIG) distribution. The second objective, therefore, is to construct and obtain properties of the NWIG distribution. The maximum likelihood parameter estimates of the proposed model are estimated via EM algorithm and three data sets are used for application. The result shows that the proposed model is flexible and fits the data well.

INVERSE POWER METHOD AND WEIGHTED SOBOLEV SPACES

1. Introduction This paper is a continuation of the paper [5]. Now we want to treat the problem

Moore-Penrose Inverse and Semilinear Equations

In this paper, we study the existence of solutions for the semilinear equation , where A is a , , and is a nonlinear continuous function. Assuming that the Moore-Penrose inverse AT(AAT)-1?exists (A denotes the transposed matrix of A) which is true whenever the determinant of the matrix AAT is different than zero, and the following condition on the nonlinear term satisfied . We prove that the semilinear equation has solutions for all. Moreover, these solutions can be found from the following fixed point relation .

Reservoir parameter inversion based on weighted statistics

Variation of reservoir physical properties can cause changes in its elastic parameters. However, this is not a simple linear relation. Furthermore, the lack of observations, data overlap, noise interference, and idealized models increases the uncertainties of the inversion result. Thus, we propose an inversion method that is different from traditional statistical rock physics modeling. First, we use deterministic and stochastic rock physics models considering the uncertainties of elastic parameters obtained by prestack seismic inversion and introduce weighting coefficients to establish a weighted statistical relation between reservoir and elastic parameters. Second, based on the weighted statistical relation, we use Markov chain Monte Carlo simulations to generate the random joint distribution space of reservoir and elastic parameters that serves as a sample solution space of an objective function. Finally, we propose a fast solution criterion to maximize the posterior probability density and obtain reservoir parameters. The method has high efficiency and application potential.

Application of Artificial Neural Network, Kriging, and Inverse Distance Weighting Models for Estimation of Scour Depth around Bridge Pier with Bed Sill

This paper outlines the application of the multi-layer perceptron artificial neural network (ANN), ordinary kriging (OK), and inverse distance weighting (IDW) models in the estimation of local scour depth around bridge piers. As part of this study, bridge piers were installed with bed sills at the bed of an experimental flume. Experimental tests were conducted under different flow conditions and varying distances between bridge pier and bed sill. The ANN, OK and IDW models were applied to the experimental data and it was shown that the artificial neural network model predicts local scour depth more accurately than the kriging and inverse distance weighting models. It was found that the ANN with two hidden layers was the optimum model to predict local scour depth. The results from the sixth test case showed that the ANN with one hidden layer and 17 hidden nodes was the best model to predict local scour depth. Whereas the results from the fifth test case found that the ANN with three hidden layers was the best model to predict local scour depth.

Inverse nodal problem for the Sturm-Liouville operator with a weight

In this work,we consider the inverse nodal problem for the Sturm-Liouville problem with a weight and the jump condition at the middle point.It is shown that the dense nodes of the eigenfunctions can uniquely determine the potential on the whole interval and some parameters.

Evaluating gravity gradient components based on a reweighted inversion method

In gravity gradient inversion,to choose an appropriate component combination is very important,that needs to understand the function of each component of gravity gradient in the inversion.In this paper,based on the previous research on the characteristics of gravity gradient components,we propose a reweighted inversion method to evaluate the influence of single gravity gradient component on the inversion resolution The proposed method only adopts the misfit function of the regularized equation and introduce a depth weighting function to overcome skin effect produced in gravity gradient inversion.A comparison between different inversion results was undertaken to verify the influence of the depth weighting function on the inversion result resolution.To avoid the premise of introducing prior information,we select the depth weighting function based on the sensitivity matrix.The inversion results using the single-prism model and the complex model show that the influence of different components on the resolution of inversion results is different in different directions,however,the inversion results based on two kind of models with adding different levels of random noise are basically consistent with the results of inversion without noises.Finally,the method was applied to real data from the Vinton salt dome,Louisiana,USA.

Study on the Concentration Inversion of NO &NO2 Gas from the Vehicle Exhaust Based on Weighted PLS

It becomes a key technology to measure the concentration of the vehicle exhaust components with the absorption spectra. But because of the overlap of gas absorption bands, how to separate the absorption information of each component gas from the mixed absorption spectra has become the key point to restrict the precision of the optical detection method. In this paper, the ex-perimental platform for the absorption spectrum of vehicle exhaust components has been established. Based on the ultraviolet absorption spectra measured with the platform of exhaust gas NO & NO2, the concentration regression model for the two components has been established with weighted partial least squares regression (WPLS). Finally the each spectral characteristic information of NO & NO2 gas has been separated and the concentration of each corresponding component has been reversed successfully.

Diffusion-weighted imaging and fluid-attenuated inversion recovery sequence in sporadic Creutzfeldt-Jakob disease:One-case report

The diagnosis of sporadic Creutzfeldt-Jakob disease （sCJD） is extremely difficult. Diffusion-weighted imaging has been shown to be the most sensitive technique for the detection of signal alterations in sCJD patients. The present study analyzed the diagnostic value of diffusion-weighted imaging and fluid-attenuated inversion recovery sequence in the early stage of sCJD in one female patient and correlated the clinical symptoms during disease course and magnetic resonance manifestations. Thalamic and basal ganglia hyperintensities were observed on magnetic resonance images in a very early stage, i.e., when the clinical typical manifestations of the disease were not present. With the progression of the disease, cortical and basal ganglia hyperintensities were observed on magnetic resonance images, showing an obvious cerebral atrophy. These findings suggest that diffusion-weighted imaging and fluid-attenuated inversion recovery sequence are helpful in diagnosing sCJD.