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Selective phytochemicals targeting pancreatic stellate cells as new anti-fibrotic agents for chronic pancreatitis and pancreatic cancer

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Acta Pharmaceutica Sinica B 2020年第3期10卷 399-413页

作者： Puvanesswaray Ramakrishnan wei Mee Loh Subash CBGopinath Srinivasa Reddy Bonam Ismail M.Fareez Rhanye Mac Guad Maw shin Sim Yuan Seng Wu Ageing and Age-Associated Disorders Research Group Faculty of MedicineUniversity of MalayaKuala Lumpur 50603Malaysia Depanment of Pharmacology Faculty of MedicineUniversity of MalayaKuala Lumpur 50603Malaysia School of Bioprocess Engineering Universiti Malaysia PerlisArau 02600Malaysia Institute of Nano Electronic Engineering Universiti Malaysia PerlisKangar 01000Malaysia UMR 7242 CNRS-University of StrasbourgBiotechnology and Cell Signaling/Laboratory of Excellence MedalisIllkirch 67400France Department of Oral Biology and Biomedical Sciences Faculty of DentistryMAHSA UniversitySelangor 42610Malaysia Department of Biomedical Science and Therapeutics Faculty of Medicine and Health ScienceUniversiti Malaysia SabahKota Kinabalu 88400Malaysia Department of Pharmaceutical Life Sciences Faculty of PharmacyUniversity of MalayaKuala Lumpur 50603Malaysia Department of Biochemistry Faculty of Medicine Bioscience and NursingMAHSA UniversitySelangor 42610Malaysia

Activated pancreatic stellate cells(PSCs)have been widely accepted as a key precursor of excessive pancreatic fibrosis,which is a crucial hallmark of chronic pancreatitis(CP)and its formidable associated disease,pancreatic cancer(PC).Hence,anti-fibrotic therapy has been identified as a novel therapeutic strategy for treating CP and PC by targeting *** of the anti-fibrotic agents have been limited to phaseⅠ/Ⅱclinical trials involving vitamin analogs,which are abundant in medicinal plants and have proved to be promising for clinical *** use of phytomedicines,as new anti-fibrotic agents,has been applied to a variety of complementary and alternative *** aim of this review was to present a focused update on the selective new potential anti-fibrotic agents,including curcumin,resveratrol,rhein,emodin,green tea catechin derivatives,metformin,eruberin A,and ellagic acid,in combating PSC in CP and PC *** aimed to describe the mechanism(s)of the phytochemicals used,either alone or in combination,and the associated molecular *** of them were tested in PC models with similar mechanism of actions,and curcumin was tested *** research may explore the issues of bioavailability,drug design,and nano-formulation,in order to achieve successful clinical outcomes with promising activity and tolerability.

关键词： Pancreatic stellate cells Anti-fibrotic Chronic pancreatitis Pancreatic cancer Phytochemicals Curcumin Resverastrol Rhein Emodin Green tea catechin

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Standard Embeddings of Smooth Schubert Varieties in Rational Homogeneous Manifolds of Picard Number 1

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Acta Mathematica Sinica,English Series 2018年第3期34卷 466-487页

作者： shin-Young KIM Kyeong-Dong PARK Department of Mathematics and Statistics Masaryk University Brno Czech Center for Geometry and Physics Institute for Basic Science ( IBS) Pohang Korea

Smooth Schubert varieties in rational homogeneous manifolds of Picard number 1 are horospherical varieties. We characterize standard embeddings of smooth Schubert varieties in rational homogeneous manifolds of Picard number 1 by means of varieties of minimal rational tangents. In particular, we mainly consider nonhomogeneous smooth Schubert varieties in symplectic Grassmannians and in the 20-dimensional F_4- homogeneous manifold associated to a short simple root.

关键词： Smooth Schubert varieties rational homogeneous manifolds variety of minimal rational tangents standard embeddings Cartan-Fubini extension

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Wiener's lemma:localization and various approaches

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Applied Mathematics(A Journal of Chinese Universities) 2013年第4期28卷 465-484页

作者： shin Chang Eon SUN Qi-yu Department of Mathematics Sogang UniversitySeoul 121-742 Korea Department of Mathematics University of Central FloridaOrlando FL 32816 USA

Matrices and integral operators with off-diagonal decay appear in numerous areas of mathematics including numerical analysis and harmonic analysis, and they also play impor-tant roles in engineering science including signal processing and communication engineering. Wiener’s lemma states that the localization of matrices and integral operators are preserved un-der inversion. In this introductory note, we re-examine several approaches to Wiener’s lemma for matrices. We also review briefly some recent advances on localization preservation of operations including nonlinear inversion, matrix factorization and optimization.

关键词： Wiener’s lemma infinite matrix stability Wiener algebra Beurling algebra off-diagonal decay inverse closedness

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Journal of Central South University 2013年第9期20卷 2440-2446页

作者： LEE Sang-hyuk shin Seung-soo Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Department of Information Security Tongmyong University

Similarity measure design on non-overlapped data was carried out and compared with the case of overlapped *** feature of similarity on overlapped data to non-overlapped data was provided by *** the artificial data illustration,it was proved that the conventional similarity measure was not proper to calculate the similarity measure of the non-overlapped *** overcome the unbalance problem,similarity measure on non-overlapped data was obtained by considering neighbor ***,different approaches to design similarity measure were proposed and proved by consideration of neighbor *** the example of artificial data,similarity measure calculation was carried *** measure extension to intuitionistic fuzzy sets(IFSs)containing uncertainty named hesitance was also followed.

关键词： similarity measure overlapped data non-overlapped data intuitionistic data

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Visual attention and clustering-based automatic selection of landmarks using single camera

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Journal of Central South University 2014年第9期21卷 3525-3533页

作者： CHUHO Yi YONGMIN shin JUNGWON Cho Future IT R&D Lab LG Electronics Home Appliance R&D Lab LG ElectronicsSeoul 153721 Korea Department of Computer Education Jeju National University Department of Mathematics and Computer Science Salisbury University

An improved method with better selection capability using a single camera was presented in comparison with previous method. To improve performance, two methods were applied to landmark selection in an unfamiliar indoor environment. First, a modified visual attention method was proposed to automatically select a candidate region as a more useful landmark. In visual attention, candidate landmark regions were selected with different characteristics of ambient color and intensity in the image. Then, the more useful landmarks were selected by combining the candidate regions using clustering. As generally implemented, automatic landmark selection by vision-based simultaneous localization and mapping(SLAM) results in many useless landmarks, because the features of images are distinguished from the surrounding environment but detected repeatedly. These useless landmarks create a serious problem for the SLAM system because they complicate data association. To address this, a method was proposed in which the robot initially collected landmarks through automatic detection while traversing the entire area where the robot performed SLAM, and then, the robot selected only those landmarks that exhibited high rarity through clustering, which enhanced the system performance. Experimental results show that this method of automatic landmark selection results in selection of a high-rarity landmark. The average error of the performance of SLAM decreases 52% compared with conventional methods and the accuracy of data associations increases.

关键词： simultaneous localization and mapping automatic landmark selection visual attention clustering

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Tensor based non-photo realistic rendering for Korean architectural images

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Journal of Central South University 2014年第10期21卷 3805-3810页

作者： Do Kyung shin Eun Young Ahn Deprtment of Computer Science and Engineering Hanyang University Deprtment of Communication Infromation & Computer Engineering Hanbat National University

Existing pen and ink sketch technologies can be applied to general images, but they could not produce optimal output for images of traditional architecture, because most images consist of exquisite straight lined patterns in traditional architecture, such as root tiles and window bars. The lines of roofs and eaves need to be described delicately to express pen and ink sketch most effectively. Therefore, by proposing a method to create white noise for light and shade of input images, to extract input vector directions from the white noise, and to determine the direction and length of stroke, a new expression technique is proposed for pen and ink sketch that could best reflect the characteristics of traditional architecture.

关键词： non-photo realistic rendering pen and ink sketch tensor

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Feature-aware regularization for sparse online learning

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Science China(Information Sciences) 2014年第5期57卷 65-85页

作者： OIWA Hidekazu MATSUSHIMA shin NAKAGAWA Hiroshi Graduate School of Information Science and Technology The University of Tokyo Information Technology Center The University of Tokyo

Learning a compact predictive model in an online setting has recently gained a great deal of *** combination of online learning with sparsity-inducing regularization enables faster learning with a smaller memory space than the previous learning *** optimization methods and learning algorithms have been developed on the basis of online learning with L1-regularization.L1-regularization tends to truncate some types of parameters,such as those that rarely occur or have a small range of values,unless they are emphasized in ***,the inclusion of a pre-processing step would make it very difficult to preserve the advantages of online *** propose a new regularization framework for sparse online *** focus on regularization terms,and we enhance the state-of-the-art regularization approach by integrating information on all previous subgradients of the loss function into a regularization *** resulting algorithms enable online learning to adjust the intensity of each feature’s truncations without pre-processing and eventually eliminate the bias of *** show theoretical properties of our framework,the computational complexity and upper bound of *** demonstrated that our algorithms outperformed previous methods in many classification tasks.

关键词： online learning supervised learning sparsity-inducing regularization feature selection sentiment analysis

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Least-squares finite-element method for shallow-water equations with source terms

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Acta Mechanica Sinica 2009年第5期25卷 597-610页

作者： shin-Jye Liang Tai-Wen Hsu Department of Marine Environmental lnformatics National Taiwan Ocean University Department of Hydraulic and Ocean Engineering National Cheng Kung University

Numerical solution of shallow-water equations （SWE） has been a challenging task because of its nonlinear hyperbolic nature, admitting discontinuous solution, and the need to satisfy the C-property. The presence of source terms in momentum equations, such as the bottom slope and friction of bed, compounds the difficulties further. In this paper, a least-squares finite-element method for the space discretization and θ-method for the time integration is developed for the 2D non-conservative SWE including the source terms. Advantages of the method include： the source terms can be approximated easily with interpolation functions, no upwind scheme is needed, as well as the resulting system equations is symmetric and positive-definite, therefore, can be solved efficiently with the conjugate gradient method. The method is applied to steady and unsteady flows, subcritical and transcritical flow over a bump, 1D and 2D circular dam-break, wave past a circular cylinder, as well as wave past a hump. Computed results show good C-property, conservation property and compare well with exact solutions and other numerical results for flows with weak and mild gradient changes, but lead to inaccurate predictions for flows with strong gradient changes and discontinuities.

关键词： Shallow-water equations Source terms Least-squares finite-element method Dam-break C-property

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Learning excited states from ground states by using an artificial neural network

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npj Computational Materials 2020年第1期6卷 1056-1061页

作者： shin Kiyohara Masashi Tsubaki Teruyasu Mizoguchi Institute of Industrial Science University of Tokyo153-8505 TokyoJapan National Institute of Advanced Industrial Science and Technology(AIST) 135-0064 TokyoJapan

Excited states are different quantum states from their ground states,and spectroscopy methods that can assess excited states are widely used in materials *** the spectra reflecting excited states is thus of great importance for materials ***,understanding such spectra remains difficult because excited states have usually different atomic or electronic configurations from their corresponding ground *** excited states could be predicted from ground states,the knowledge of the excited states would be ***,we used an artificial neural network to predict the excited states of the core-electron absorption spectra from their ground ***,our model correctly learned and predicted the excited states from their ground states,providing several thousand times computational ***,it showed excellent transferability to other ***,we found two physical insights about excited states:core-hole effects of amorphous silicon oxides are stronger than those of crystalline silicon oxides,and the excited-ground states relationships of some metal oxides are similar to those of the silicon oxides,which could not be obtained by conventional spectral simulation nor found until using machine leaning.

关键词： ground artificial oxides

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Video learning based image classification method for object recognition

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Journal of Central South University 2013年第9期20卷 2399-2406页

作者： LEE Hong-ro shin Yong-ju Department of NTIS Center Korea Institute of Science & Technology Information

Automatic image classification is the first step toward semantic understanding of an object in the computer vision *** key challenge of problem for accurate object recognition is the ability to extract the robust features from various viewpoint images and rapidly calculate similarity between features in the image database or video *** order to solve these problems,an effective and rapid image classification method was presented for the object recognition based on the video learning *** optical-flow and RANSAC algorithm were used to acquire scene images from each video *** the selection of scene images,the local maximum points on comer of object around local area were found using the Harris comer detection algorithm and the several attributes from local block around each feature point were calculated by using scale invariant feature transform （SIFT） for extracting local ***,the extracted local descriptor was learned to the three-dimensional pyramid match *** results show that our method can extract features in various multi-viewpoint images from query video and calculate a similarity between a query image and images in the database.

关键词： image classification multi-viewpoint image feature extraction video learning

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