Applied Mathematics-A Journal of Chinese Universities Series B最新文献_第7页

Unilateral global interval bifurcation for problem with mean curvature operator in Minkowski space and its applications Minkowski空间中平均曲率算子问题的单边全局区间分岔及其应用

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2022-06-16 DOI: 10.1007/s11766-022-3580-0

Wen-guo Shen

{"title":"Unilateral global interval bifurcation for problem with mean curvature operator in Minkowski space and its applications","authors":"Wen-guo Shen","doi":"10.1007/s11766-022-3580-0","DOIUrl":"10.1007/s11766-022-3580-0","url":null,"abstract":"<div>In this paper, we establish a unilateral global bifurcation result from interval for a class problem with mean curvature operator in Minkowski space with non-differentiable nonlinearity. As applications of the above result, we shall prove the existence of one-sign solutions to the following problem <div><div>$$left{ {matrix{{ - {rm{div}}left( {{{nabla v} over {sqrt {1 - {{left| {nabla v} right|}^2}} }}} right) = alpha (x){v^ + } + beta (x){v^ - } + lambda a(x)f(v),} hfill & {{rm{in}},{B_R}(0),} hfill cr {v(x) = 0,} hfill & {{rm{on}},partial {B_R}(0),} hfill cr } } right.$$</div></div> where λ ≠ 0 is a parameter, R is a positive constant and BR(0) = {x ∈ ℝN: ∣x∣ < R} is the standard open ball in the Euclidean space ℝN (N ≥ 1) which is centered at the origin and has radius R. v+ = max{v, 0},v− = − min{v, 0}, (a(x) in C(overline {{B_R}(0)} ), a(x), α(x) and β(x) are radially symmetric with respect to x; f ∈ C(ℝ, ℝ), sf(s) > 0 for s ≠ 0, and f0 ∈ [0, ∞], where f0 = lim∣s∣→0f(s)/s. We use unilateral global bifurcation techniques and the approximation of connected components to prove our main results. We also study the asymptotic behaviors of positive radial solutions as λ → +∞.</div>","PeriodicalId":55568,"journal":{"name":"Applied Mathematics-A Journal of Chinese Universities Series B","volume":"37 2","pages":"159 - 176"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44261787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

On ideal convergence of double sequences in 2—fuzzy n—normed linear space 2 -模糊n赋范线性空间中二重序列的理想收敛性

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2022-06-16 DOI: 10.1007/s11766-022-3771-8

Vakeel A. Khan, Sameera A. A. Abdullah, Kamal M. A. S. Alshlool, Umme Tuba, Nazneen Khan

引用次数: 0

Zero-inflated non-central negative binomial distribution 零膨胀非中心负二项分布

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2022-06-16 DOI: 10.1007/s11766-022-4070-0

Wei-zhong Tian, Ting-ting Liu, Yao-ting Yang

引用次数: 2

Facial landmark disentangled network with variational autoencoder 基于变分自编码器的人脸标记解纠缠网络

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2022-06-16 DOI: 10.1007/s11766-022-4589-0

Sen Liang, Zhi-ze Zhou, Yu-dong Guo, Xuan Gao, Ju-yong Zhang, Hu-jun Bao

{"title":"Facial landmark disentangled network with variational autoencoder","authors":"Sen Liang, Zhi-ze Zhou, Yu-dong Guo, Xuan Gao, Ju-yong Zhang, Hu-jun Bao","doi":"10.1007/s11766-022-4589-0","DOIUrl":"10.1007/s11766-022-4589-0","url":null,"abstract":"<div>Learning disentangled representation of data is a key problem in deep learning. Specifically, disentangling 2D facial landmarks into different factors (e.g., identity and expression) is widely used in the applications of face reconstruction, face reenactment and talking head et al.. However, due to the sparsity of landmarks and the lack of accurate labels for the factors, it is hard to learn the disentangled representation of landmarks. To address these problem, we propose a simple and effective model named FLD-VAE to disentangle arbitrary facial landmarks into identity and expression latent representations, which is based on a Variational Autoencoder framework. Besides, we propose three invariant loss functions in both latent and data levels to constrain the invariance of representations during training stage. Moreover, we implement an identity preservation loss to further enhance the representation ability of identity factor. To the best of our knowledge, this is the first work to end-to-end disentangle identity and expression factors simultaneously from one single facial landmark.</div>","PeriodicalId":55568,"journal":{"name":"Applied Mathematics-A Journal of Chinese Universities Series B","volume":"37 2","pages":"290 - 305"},"PeriodicalIF":0.0,"publicationDate":"2022-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11766-022-4589-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50032795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Rotary axis calculation for five-axis FDM printer using a point-fitting optimization method 用点拟合优化方法计算五轴FDM打印机的转轴

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2022-06-16 DOI: 10.1007/s11766-022-4586-3

Hao Liu, Lei Liu, Kai Shen

引用次数: 0

Convergence analysis for delay Volterra integral equation 时滞Volterra积分方程的收敛性分析

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2022-06-16 DOI: 10.1007/s11766-022-3563-1

Wei-shan Zheng

引用次数: 0

Modeling and targeting an essential metabolic pathway of Plasmodium falciparum in apicoplast using Petri nets 利用Petri网模拟和靶向恶性疟原虫在顶质体中的重要代谢途径

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2022-03-17 DOI: 10.1007/s11766-022-4413-x

Sakshi Gupta, Gajendra Pratap Singh, Sunita Kumawat

{"title":"Modeling and targeting an essential metabolic pathway of Plasmodium falciparum in apicoplast using Petri nets","authors":"Sakshi Gupta, Gajendra Pratap Singh, Sunita Kumawat","doi":"10.1007/s11766-022-4413-x","DOIUrl":"10.1007/s11766-022-4413-x","url":null,"abstract":"<div>Petri net (PN) is one of the promising computational and mathematical formalisms used to represent and study the behavior of complex metabolic networks. The various available analysis techniques of PN could be used to validate and analyze the network in different scenarios. Plasmodium falciparum is one of the threatening parasites which causes malaria, a deadly disease affecting a large number of today’s world population. The development of antimalarial drug resistance is an emerging global threat, highlighting the need to discover novel antimalarial targets. The fatty acid biosynthesis of malarial parasite is one of the essential metabolic pathways required for its growth and is present in apicoplast, a non-photosynthetic plastid. The malarial parasite obtains fatty acids by using type two fatty acid synthase (FAS II) enzyme, which is different from type one enzyme used by human host, making it an ideal drug target. This article proposes and studies the PN model of the parasite’s FAS II pathway to analyze the mechanism of potential drug targets in this pathway. The proposed PN model can serve as a base for further findings in the field of antimalarial drug targets to decrease the malaria mortality rate.</div>","PeriodicalId":55568,"journal":{"name":"Applied Mathematics-A Journal of Chinese Universities Series B","volume":"37 1","pages":"91 - 110"},"PeriodicalIF":0.0,"publicationDate":"2022-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50035295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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: 2

Learning a Discriminative Feature Attention Network for pancreas CT segmentation 胰腺CT分割的判别特征注意网络学习

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2022-03-17 DOI: 10.1007/s11766-022-4346-4

Mei-xiang Huang, Yuan-jin Wang, Chong-fei Huang, Jing Yuan, De-xing Kong

{"title":"Learning a Discriminative Feature Attention Network for pancreas CT segmentation","authors":"Mei-xiang Huang, Yuan-jin Wang, Chong-fei Huang, Jing Yuan, De-xing Kong","doi":"10.1007/s11766-022-4346-4","DOIUrl":"10.1007/s11766-022-4346-4","url":null,"abstract":"<div>Accurate pancreas segmentation is critical for the diagnosis and management of diseases of the pancreas. It is challenging to precisely delineate pancreas due to the highly variations in volume, shape and location. In recent years, coarse-to-fine methods have been widely used to alleviate class imbalance issue and improve pancreas segmentation accuracy. However, cascaded methods could be computationally intensive and the refined results are significantly dependent on the performance of its coarse segmentation results. To balance the segmentation accuracy and computational efficiency, we propose a Discriminative Feature Attention Network for pancreas segmentation, to effectively highlight pancreas features and improve segmentation accuracy without explicit pancreas location. The final segmentation is obtained by applying a simple yet effective post-processing step. Two experiments on both public NIH pancreas CT dataset and abdominal BTCV multi-organ dataset are individually conducted to show the effectiveness of our method for 2D pancreas segmentation. We obtained average Dice Similarity Coefficient (DSC) of 82.82±6.09%, average Jaccard Index (JI) of 71.13± 8.30% and average Symmetric Average Surface Distance (ASD) of 1.69 ± 0.83 mm on the NIH dataset. Compared to the existing deep learning-based pancreas segmentation methods, our experimental results achieve the best average DSC and JI value.</div>","PeriodicalId":55568,"journal":{"name":"Applied Mathematics-A Journal of Chinese Universities Series B","volume":"37 1","pages":"73 - 90"},"PeriodicalIF":0.0,"publicationDate":"2022-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11766-022-4346-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50035296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Recent advances in statistical methodologies in evaluating program for high-dimensional data 高维数据评估程序中统计方法的最新进展

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2022-03-17 DOI: 10.1007/s11766-022-4489-3

Ming-feng Zhan, Zong-wu Cai, Ying Fang, Ming Lin

{"title":"Recent advances in statistical methodologies in evaluating program for high-dimensional data","authors":"Ming-feng Zhan, Zong-wu Cai, Ying Fang, Ming Lin","doi":"10.1007/s11766-022-4489-3","DOIUrl":"10.1007/s11766-022-4489-3","url":null,"abstract":"<div>The era of big data brings opportunities and challenges to developing new statistical methods and models to evaluate social programs or economic policies or interventions. This paper provides a comprehensive review on some recent advances in statistical methodologies and models to evaluate programs with high-dimensional data. In particular, four kinds of methods for making valid statistical inferences for treatment effects in high dimensions are addressed. The first one is the so-called doubly robust type estimation, which models the outcome regression and propensity score functions simultaneously. The second one is the covariate balance method to construct the treatment effect estimators. The third one is the sufficient dimension reduction approach for causal inferences. The last one is the machine learning procedure directly or indirectly to make statistical inferences to treatment effect. In such a way, some of these methods and models are closely related to the de-biased Lasso type methods for the regression model with high dimensions in the statistical literature. Finally, some future research topics are also discussed.</div>","PeriodicalId":55568,"journal":{"name":"Applied Mathematics-A Journal of Chinese Universities Series B","volume":"37 1","pages":"131 - 146"},"PeriodicalIF":0.0,"publicationDate":"2022-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s11766-022-4489-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"50034808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Symmetry and monotonicity of positive solutions to Schrödinger systems with fractional p-Laplacians 分数阶p-拉普拉斯Schrödinger系统正解的对称性和单调性

4区数学

Applied Mathematics-A Journal of Chinese Universities Series B Pub Date : 2022-03-17 DOI: 10.1007/s11766-022-4263-6

Ling-wei Ma, Zhen-qiu Zhang

引用次数: 0