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Solitary extraovarian primary peritoneal carcinoma with direct invasion into the liver,diaphragm and lung without peritoneal dissemination or distant metastasis

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Hepatobiliary & Pancreatic Diseases International 2024年第3期23卷 322-325页

作者： Billy Ho hung Cheung Wong Hoi She Siu Lun Ho Albert Chi yan Chan Chung Mau Lo Tan To Cheung Department of Surgery The University of Hong KongHong KongChina Department of Pathology The University of Hong KongHong KongChina

To the Editor:Extraovarian primary peritoneal carcinoma(EOPPC)is an uncommon malignancy with many similarities to epithelial ovarian carcinoma in histological,clinical,and etiological aspects[1].This phenomenon is explained by their common embryonal origin,in which both develop from the coelomic epithelium in the early embryological *** their similarities,the incidence of EOPPC is significantly lower than that of epithelial ovarian carcinoma(6.78 cases per million vs.120.5 cases per million)[1].

关键词： peritoneal invasion metastasis

Identifying Brand Consistency by Product Differentiation Using CNN

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 685-709页

作者： hung-Hsiang Wang Chih-Ping Chen Department of Industrial Design National Taipei University of TechnologyTaipeiTaiwan Department of Product Design Ming Chuan UniversityTaoyuanTaiwan

This paper presents a new method of using a convolutional neural network(CNN)in machine learning to identify brand consistency by product appearance *** Experiment 1,we collected fifty mouse devices from the past thirty-five years from a renowned company to build a dataset consisting of product pictures with pre-defined design features of their appearance and *** show that it is a challenge to distinguish periods for the subtle evolution of themouse devices with such traditionalmethods as time series analysis and principal component analysis(PCA).In Experiment 2,we applied deep learning to predict the extent to which the product appearance variation ofmouse devices of various *** investigation collected 6,042 images ofmouse devices and divided theminto the Early Stage and the Late *** show the highest accuracy of 81.4%with the CNNmodel,and the evaluation score of brand style consistency is 0.36,implying that the brand consistency score converted by the CNN accuracy rate is not always perfect in the real *** relationship between product appearance variation,brand style consistency,and evaluation score is beneficial for predicting new product styles and future product style *** addition,the CNN heat maps highlight the critical areas of design features of different styles,providing alternative clues related to the blurred *** study provides insights into practical problems for designers,manufacturers,and marketers in product *** not only contributes to the scientific understanding of design development,but also provides industry professionals with practical tools and methods to improve the design process and maintain brand *** can use these techniques to find features that influence brand ***,capture these features as innovative design elements and maintain core brand values.

关键词： Machine learning product differentiation brand consistency principal component analysis convolutional neural network computer mouse

Unique anti-angiogenic effects,pharmacological targets and therapeutic mechanisms of Chinese herbal medicines for endometriosis

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Genes & Diseases 2024年第5期11卷 63-65页

作者： Bo Liang Rui Dong Sze Wan hung Yiran Li Yuezhen Lin ling Wu Tao Zhang Gene Chi Wai Man Hui Xu Jacqueline Pui Wah Chung Chi Chiu Wang Guangdong Provincial Key Laboratory of Marine Biotechnology Institute of Marine SciencesShantou UniversityShantouGuangdong 515063China Department of Obstetrics and Gynaecology The Chinese University of Hong KongHong Kong SARChina Reproduction and Development Laboratory Li Ka Shing Institute of Health SciencesThe Chinese University of Hong KongHong Kong SARChina School of Biomedical Sciences The Chinese University of Hong KongHong Kong SARChina Chinese University of Hong Kong-Sichuan University Joint Laboratory in Reproductive Medicine The Chinese University of Hong KongHong Kong SARChina

Endometriosis is a common and benign angiogenesisdependent gynecological disorder,which refers to the proliferation and growth of endometrium-like tissues with neovasculature formation outside of the uterus.1 Available medical treatments for endometriosis containing hormonal and non-hormonal treatments had been limited for longterm usage by their side effects.2 Ideal medical treatment for endometriosis with efficacy to relieve symptoms and suppress endometriotic lesion growth and minimal side effects has been longing for decades.3 Angiogenesis is a promising therapeutic target for endometriosis.

关键词： therapeutic endometriosis herbal

Experimental preparation of topologically ordered states via adiabatic evolution

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Science China(Physics,Mechanics & Astronomy) 2019年第8期62卷 39-45页

作者： ZhiHuang Luo Jun Li ZhaoKai Li ling-yan hung Yi Dun Wan XinHua Peng JiangFeng Du Beijing Computational Science Research Center CAS Key Laboratory of Microscale Magnetic Resonance and Department of Modern Physics University of Science and Technology of China Department of Physics and Institute for Quantum Science and Engineering Southern University of Science and Technology State Key Laboratory of Surface Physics and Department of Physics Fudan University Department of Physics and Center for Field Theory and Particle Physics Fudan University Collaborative Innovation Center of Advanced Microstructures Nanjing University Perimeter Institute for Theoretical Physics Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of China

Topological orders are a class of exotic states of matter characterized by patterns of long-range entanglement. Certain topologically ordered systems are proposed as potential realization of fault-tolerant quantum computation. Topological orders can arise in two-dimensional spin-lattice models. In this paper, we engineer a time-dependent Hamiltonian to prepare a topologically ordered state through adiabatic evolution. The other sectors in the degenerate ground-state space of the model are obtained by applying nontrivial operations corresponding to closed string operators. Each sector is highly entangled, as shown from the completely reconstructed density matrices. This paves the way towards exploring the properties of topological orders and the application of topological orders in topological quantum memory.

关键词： topologically ordered state adiabatic evolution nuclear magnetic resonance

Exponentially Bounded C-semigroup and the Cauchy Initial Value Problems in Complete Random Normed Modules

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Acta Mathematica Sinica,English Series 2024年第9期40卷 2195-2212页

作者： Son TA CONG Thang Dang hung Oanh Le THI Department of Mathematics University of ScienceVietnam National University 334 Nguyen TraiThanh XuanHanoiVietnam Faculty of Natural Sciences Hong Duc University565 Quang TrungDong VeThanh HoaVietnam

In this paper,the notion of C-semigroup of continuous module homomorphisms on a complete random normal(RN)module is introduced and *** existence and uniqueness of solution to the Cauchy problem with respect to exponen... 详细信息

关键词： C-semigroup Cauchy problem random normed modules L^(0)-Lipschitz

Data-Driven Modeling of Partially Observed Biological Systems

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Communications on Applied Mathematics and Computation 2024年第1期6卷 739-754页

作者： Wei-hung Su Ching-Shan Chou Dongbin Xiu Department of Mathematics The Ohio State UniversityColumbusOH43221USA

We present a numerical approach for modeling unknown dynamical systems using partially observed data,with a focus on biological systems with(relatively)complex dynamical *** an extension of the recently developed deep neural network(DNN)learning methods,our approach is particularly suitable for practical situations when(i)measurement data are available for only a subset of the state variables,and(ii)the system parameters cannot be observed or measured at *** demonstrate that,with a properly designed DNN structure with memory terms,effective DNN models can be learned from such partially observed data containing hidden *** learned DNN model serves as an accurate predictive tool for system *** a few representative biological problems,we demonstrate that such DNN models can capture qualitative dynamical behavior changes in the system,such as bifurcations,even when the parameters controlling such behavior changes are completely unknown throughout not only the model learning process but also the system prediction *** learned DNN model effectively creates a“closed”model involving only the observables when such a closed-form model does not exist mathematically.

关键词： Deep neural network(DNN) Governing equation discovery Biological system Partial observation

Study of relationship between motion of mechanisms in gas operated weapon and its shock absorber

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Defence Technology（防务技术） 2024年第3期33卷 42-54页

作者： Jiri Balla Roman Vitek Dung Nguyen Van Zbynek Krist hung Nguyen Van Department of Weapons and Ammunition University of Defence BrnoCzech Republic Department of Weapons Le Quy Don Technical UniversityHanoiViet Nam Department of Design and Special Engineering Alexander Dubcek University of TrencinSlovakia

The article deals with the motion of the breech block carrier and the weapon casing of an automatic weapon mounted on a flexible carriage and the base of the *** works,which did not consider the dynamic properties of the base of the weapon,did not allow to reconcile the calculated and experimental results of the weapon casing displacement when shooting from firing *** the analysis of the motion of individual parts,the methods of mathematical modelling and firing experiments using a high-speed camera were *** show the best accord with experiment when modelling the system with 4 degrees of *** oscillation of the system regarding the movement of the breech block carrier and the weapon casing was investigated under changed conditions of rate of fire,the use of a muzzle brake and different types of shock *** velocities and displacements of the weapon casing and the breech block carrier at different values of the impulse of the gases to the breech block carrier were determined.

关键词： Shock absorber Gas-operated weapon Force-impulse diagram Recoil system Breech block carrier

Exploring the entanglement of free spin-(1/2), spin-1 and spin-2 fields

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Chinese Physics C 2019年第5期43卷 12-22页

作者：杨智孔令欣 Department of Physics & Center for Field Theory and Particle Physics Fudan University State Key Laboratory of Surface Physics & Department of Physics Fudan University

In this study, we explore the entanglement of free spin-(1/2), spin-1, and spin-2 fields. We start with an example involving Majorana fields in 1+1 and 2+1 dimensions. Subsequently, we perform the Bogoliubov transformation and express the vacuum state with a particle pair state in the configuration space, which is used to calculate the entropy. This clearly demonstrates that the entanglement entropy originates from the particles across the ***, we generalize this method to free spin-1 and spin-2 fields. These higher free massless spin fields have wellknown complications owing to gauge redundancy. We deal with the redundancy by gauge-fixing in the light-cone gauge. We show that this gauge provides a natural tensor product structure in the Hilbert space, while surrendering explicit Lorentz invariance. We also use the Bogoliubov transformation to calculate the entropy. The area law emerges naturally by this method.

关键词： entanglement Bogoliubov transformation tensor product structure

Heterogeneous decentralised machine unlearning with seed model distillation

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CAAI Transactions on Intelligence Technology 2024年第3期9卷 608-619页

作者： Guanhua Ye Tong Chen Quoc Viet hung Nguyen Hongzhi Yin School of Information Technology and Electrical Engineering The University of QueenslandSt LuciaQueenslandAustralia School of Information and Communication Technology Griffith UniversityBrisbaneQueenslandAustralia

As some recent information security legislation endowed users with unconditional rights to be forgotten by any trained machine learning model,personalised IoT service pro-viders have to put unlearning functionality into their *** most straight-forward method to unlearn users'contribution is to retrain the model from the initial state,which is not realistic in high throughput applications with frequent unlearning *** some machine unlearning frameworks have been proposed to speed up the retraining process,they fail to match decentralised learning scenarios.A decentralised unlearning framework called heterogeneous decentralised unlearning framework with seed(HDUS)is designed,which uses distilled seed models to construct erasable en-sembles for all ***,the framework is compatible with heterogeneous on-device models,representing stronger scalability in real-world *** experiments on three real-world datasets show that our HDUS achieves state-of-the-art performance.

关键词： data mining data privacy machine learning