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A New Two-grid Algorithm Based on Newton Iteration for the Stationary Navier–Stokes Equations with Damping 带阻尼平稳Navier-Stokes方程的牛顿迭代双网格算法
3区 数学 Q2 MATHEMATICS Pub Date : 2023-09-01 DOI: 10.1007/s11464-021-0018-6
Bo Zheng, Yueqiang Shang
Based on finite element discretization, a new two-grid algorithm based on Newton iteration is proposed to solve the stationary Navier–Stokes equations with nonlinear damping term. The proposed new two-grid algorithm consists of three steps: in the first step, we solve one small nonlinear coarse grid problem, and then, in the second and third steps, we solve two linear fine grid problems based on Newton iteration which have the same stiffness matrices with only different right-hand sides. We analyze stability of the present algorithm and prove rate of convergence of the approximate solutions obtained from the algorithm. Numerical results are given to demonstrate the effectiveness of the present algorithm, showing that our algorithm greatly improves the accuracy of the approximate solutions comparable to that of the usual two-grid algorithm.
在有限元离散化的基础上,提出了一种新的基于牛顿迭代的两网格算法来求解具有非线性阻尼项的平稳Navier-Stokes方程。本文提出的两网格算法分为三步:第一步求解一个小的非线性粗网格问题,第二步和第三步分别求解两个基于牛顿迭代的线性细网格问题,这两个问题具有相同的刚度矩阵,只是右侧不同。我们分析了该算法的稳定性,并证明了该算法得到的近似解的收敛速度。数值结果表明,该算法的有效性,与常用的双网格算法相比,大大提高了近似解的精度。
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引用次数: 0
Performance of 18F-DCFPyL PET/CT in Primary Prostate Cancer Diagnosis, Gleason Grading and D'Amico Classification: A Radiomics-Based Study. 18F-DCFPyL PET/CT 在原发性前列腺癌诊断、格里森分级和达米科分类中的表现:基于放射组学的研究。
IF 0.8 3区 数学 Q2 MATHEMATICS Pub Date : 2023-07-25 eCollection Date: 2023-12-01 DOI: 10.1007/s43657-023-00108-y
Yuekai Li, Fengcai Li, Shaoli Han, Jing Ning, Peng Su, Jianfeng Liu, Lili Qu, Shuai Huang, Shiwei Wang, Xin Li, Xiang Li

This study aimed to investigate the performance of 18F-DCFPyL positron emission tomography/computerized tomography (PET/CT) models for predicting benign-vs-malignancy, high pathological grade (Gleason score > 7), and clinical D'Amico classification with machine learning. The study included 138 patients with treatment-naïve prostate cancer presenting positive 18F-DCFPyL scans. The primary lesions were delineated on PET images, followed by the extraction of tumor-to-background-based general and higher-order textural features by applying five different binning approaches. Three layer-machine learning approaches were used to identify relevant in vivo features and patient characteristics and their relative weights for predicting high-risk malignant disease. The weighted features were integrated and implemented to establish individual predictive models for malignancy (Mm), high path-risk lesions (by Gleason score) (Mgs), and high clinical risk disease (by amico) (Mamico). The established models were validated in a Monte Carlo cross-validation scheme. In patients with all primary prostate cancer, the highest areas under the curve for our models were calculated. The performance of established models as revealed by the Monte Carlo cross-validation presenting as the area under the receiver operator characteristic curve (AUC): 0.97 for Mm, AUC: 0.73 for Mgs, AUC: 0.82 for Mamico. Our study demonstrated the clinical potential of 18F-DCFPyL PET/CT radiomics in distinguishing malignant from benign prostate tumors, and high-risk tumors, without biopsy sampling. And in vivo 18F-DCFPyL PET/CT can be considered a noninvasive tool for virtual biopsy for personalized treatment management.

Supplementary information: The online version contains supplementary material available at 10.1007/s43657-023-00108-y.

本研究旨在探讨18F-DCFPyL正电子发射断层扫描/计算机断层扫描(PET/CT)模型在预测良性与恶性、高病理分级(Gleason评分>7)和临床D'Amico分类方面的机器学习性能。该研究包括 138 名 18F-DCFPyL 扫描呈阳性、未经治疗的前列腺癌患者。首先在 PET 图像上对原发病灶进行划定,然后采用五种不同的分档方法提取基于肿瘤到背景的一般和高阶纹理特征。采用三种层机器学习方法确定相关的体内特征和患者特征及其相对权重,以预测高风险恶性疾病。对加权特征进行整合和实施,以建立针对恶性肿瘤(Mm)、高路径风险病变(按格里森评分)(Mgs)和高临床风险疾病(按amico)(Mamico)的单独预测模型。已建立的模型通过蒙特卡罗交叉验证方案进行了验证。在所有原发性前列腺癌患者中,我们计算出了模型的最高曲线下面积。蒙特卡洛交叉验证揭示了已建立模型的性能,即接收器运算特征曲线下面积(AUC):Mm为0.97,AUC:0.97,Mgs 的 AUC:0.73,Mamico 的 AUC:0.82:Mamico的AUC:0.82。我们的研究表明,18F-DCFPyL PET/CT 放射组学在无需活检取样的情况下区分恶性和良性前列腺肿瘤以及高危肿瘤方面具有临床潜力。体内18F-DCFPyL PET/CT可被视为虚拟活检的无创工具,用于个性化治疗管理:在线版本包含补充材料,可在 10.1007/s43657-023-00108-y.获取。
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引用次数: 0
CLTσ-group with σ-subnormal or Self-normalizing Subgroups 具有σ-次正规或自正规子群的clt σ-群
3区 数学 Q2 MATHEMATICS Pub Date : 2023-07-22 DOI: 10.1007/s11464-020-0126-8
Zhen-Lin Wu, N. Yang
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引用次数: 0
A New Characterization of the Besov Spaces Associated with Hermite Operator 与Hermite算子相关的Besov空间的一个新表征
3区 数学 Q2 MATHEMATICS Pub Date : 2023-07-22 DOI: 10.1007/s11464-020-0051-x
Ji-zheng Huang, Huixia Mo
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引用次数: 0
Further Investigation of Positive Semi-definiteness of Fourth-order Cauchy and Hilbert Tensors 四阶柯西张量和希尔伯特张量正半确定性的进一步研究
3区 数学 Q2 MATHEMATICS Pub Date : 2023-07-22 DOI: 10.1007/s11464-020-0180-2
Qingzhi Yang, Yujin Paek, Wei Mei
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引用次数: 0
Lu Qi-Keng Problem and Topological Properties of Zero Variety on the Thullen Domain 吕其庚问题及Thullen域上零变的拓扑性质
3区 数学 Q2 MATHEMATICS Pub Date : 2023-07-22 DOI: 10.1007/s11464-020-0011-5
An Wang, Chengchen Zhong
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引用次数: 0
The Finitistic Dimension and Global Dimension of an Artinian Ring with a Dualizing Complex 具有对偶化复合体的阿提尼环的有限维数和整体维数
3区 数学 Q2 MATHEMATICS Pub Date : 2023-07-22 DOI: 10.1007/s11464-020-0169-x
Yao Zhang
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引用次数: 1
The Batalin–Vilkovisky Structure over the Hochschild Cohomology Ring of Exterior Algebras 外代数Hochschild上同调环上的Batalin-Vilkovisky结构
3区 数学 Q2 MATHEMATICS Pub Date : 2023-07-22 DOI: 10.1007/s11464-020-0142-8
Weiguo Lü
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引用次数: 0
Very Regular Solution to Landau–Lifshitz–Gilbert System with Spin-polarized Transport 具有自旋极化输运的Landau-Lifshitz-Gilbert系统的正则解
3区 数学 Q2 MATHEMATICS Pub Date : 2023-07-22 DOI: 10.1007/s11464-021-0209-1
Bo Chen, Youde Wang
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引用次数: 2
Adaptive Parameter Alternating Direction Algorithm for Centrosymmetric Solutions of a Class of Generalized Coupled Sylvester-transpose Matrix Equations 一类广义耦合sylvester -转置矩阵方程中心对称解的自适应参数交替方向算法
3区 数学 Q2 MATHEMATICS Pub Date : 2023-07-22 DOI: 10.1007/s11464-020-0040-y
Tongxin Yan, Yifen Ke, Changfeng Ma
{"title":"Adaptive Parameter Alternating Direction Algorithm for Centrosymmetric Solutions of a Class of Generalized Coupled Sylvester-transpose Matrix Equations","authors":"Tongxin Yan, Yifen Ke, Changfeng Ma","doi":"10.1007/s11464-020-0040-y","DOIUrl":"https://doi.org/10.1007/s11464-020-0040-y","url":null,"abstract":"","PeriodicalId":50429,"journal":{"name":"Frontiers of Mathematics in China","volume":"38 1","pages":"977 - 998"},"PeriodicalIF":0.0,"publicationDate":"2023-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73456029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
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Frontiers of Mathematics in China
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