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Injectable Collagen/CMC Soft Tissue Filler with Developed Flow Properties

MCB Molecular and Cellular Biomechanics 2022年第2期19卷 97-104页

作者： Samanipour, Reza Pourmostafa, Aida Marzban, Adel Tabatabaee, Sara Bahraminasab, Hasan Hamidieh, Amir Ali Tavakoli, Amirhossein Department of Tissue Engineering and Applied Sciences School of Advanced Technologies in Medicine Shahid Beheshti University of Medical Sciences Tehran Iran Department of Research and Development Iranian Tissue Product Co. Tehran Iran Department of Bio-Computing Faculty of Interdisciplinary Sciences and Technologies Tarbiat Modares University Tehran Iran Iranian Tissue Bank & Research Center Gene Cell and Tissue Research Institute Tehran University of Medical Sciences Tehran Iran

Based on the remarkable demand for facial reconstitute or reshape fillers due to the dermal defects arising from specific diseases, trauma, or aging, several natural or synthetic materials have been investigated. Among the evaluated materials, decellularized dermis is one of the most biocompatible choices for the aim of skin tissue regenerative approaches. On the other hand, Carboxymethyl Cellulose (CMC), a synthetic polysaccharide, with the desirable degradability, biomechanical stability, and nontoxicity seems to be an acceptable reinforcement agent for decellularized dermis. Thus, in this research, an injectable soft tissue filler contained of human-derived decellularized collagen and CMC was fabricated. The cell-removal approving was performed utilizing H&E staining assay. The biocompatibility of the prepared samples was confirmed by MTT assay. The rheology examination demonstrated the increased storage modulus and enhanced elastic property as a consequence of CMC presence. Furthermore, the required flow force of the collagen/CMC filler was decreased as a consequence of decreasing the viscosity and its injectability was improved. According to the provided biomechanical and biological results, it could be claimed that the collagen/CMC hydrogel is a suitable substitute filler for skin tissue engineering. © 2022 Tech Science Press. All rights reserved.

关键词： Collagen

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Adaptive measurement strategy for noisy quantum amplitude estimation with variational quantum circuits

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Physical Review A 2024年第6期110卷 062423-062423页

作者： Kohei Oshio Yohichi Suzuki Kaito Wada Keigo Hisanaga Shumpei Uno Naoki Yamamoto Mizuho Research & Technologies Ltd. 2-3 Kandanishiki Chiyoda-ku Tokyo 100-8233 Japan Quantum Computing Center Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama Kanagawa 223-8522 Japan Global Research and Development Center for Business by Quantum-AI Technology (G-QuAT) National Institute of Advanced Industrial Science and Technology (AIST) 1-1-1 Umezono Tsukuba-shi Ibaraki 305-8568 Japan Department of Applied Physics and Physico-Informatics Keio University Hiyoshi 3-14-1 Kohoku-ku Yokohama 223-8522 Japan

In quantum computation, amplitude estimation is a fundamental subroutine that is utilized in various quantum algorithms. A general important task of such estimation problems is to characterize the estimation lower bound, which is referred to as quantum Cramér-Rao bound (QCRB), and to construct an optimal estimator that achieves QCRB. This paper studies the amplitude estimation in the presence of depolarizing noise with unknown intensity. The main difficulty in this problem is that the optimal measurement depends on both the unknown quantum state and the amplitude we aim to estimate. To deal with these issues, we utilize the variational quantum circuits to approximate the (unknown) optimal measurement basis combined with the two-step adaptive estimation strategy which was proposed in the quantum estimation theory. We numerically show that the proposed method can nearly attain the QCRB.

关键词： Quantum computers

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Graphical representation and hierarchical decomposition mechanism for vertex-cover solution space

arXiv

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arXiv 2019年

作者： Wei, Wei Feng, Xiangnan Wang, Jiannan Liu, Xue Zheng, Zhiming School of Mathematical Sciences Beihang University Beijing100191 China Key Laboratory of Mathematics Informatics and Behavioral Semantics Ministry of Education 100191 China Research Institute of Frontier Science Beihang University Beijing100191 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China Peng Cheng Laboratory Guangdong Shenzhen518055 China Center for Humans and Machines Max Planck Institute for Human Development Berlin14195 Germany

In this paper, solution space organization of minimum vertex-cover problem is deeply investigated using the König-Egérvary (KE) graph and theorem, in which a hierarchical decomposition mechanism named KE-layer structure of general graphs is proposed to reveal the complexity of vertex-cover. An algorithm to verify the KE graph is given by the solution space expression of vertex-cover, and the relation between multi-layer KE graphs and maximal matching is illustrated and proved. Furthermore, a framework to calculate the KE-layer number and approximate the minimal vertex-cover is provided, with different strategies of switching nodes and counting energy. The phase transition phenomenon between different KE-layers are studied with the transition points located, and searching of vertex-cover got by this strategy presents comparable advantage against several other methods. The graphical representation and hierarchical decomposition provide a new perspective to illustrate the intrinsic complexity for large-scale graphs/systems recognition. Copyright © 2019, The Authors. All rights reserved.

关键词： Graphic methods

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swTVM: Towards Optimized Tensor Code Generation for Deep Learning on Sunway Many-Core Processor

arXiv

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arXiv 2019年

作者： Li, Mingzhen Liu, Changxi Liao, Jianjin Zheng, Xuegui Yang, Hailong Sun, Rujun Xu, Jun Gan, Lin Yang, Guangwen Luan, Zhongzhi Qian, Depei School of Computer Science and Engineering Beihang University Beijing China State Key Laboratory of Software Development Environment Beijing China National University of Singapore Singapore Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing China Department of Computer Science and Technology Tsinghua University Beijing China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application portability. Among the existing deep learning compilers, TVM is well known for its efficiency in code generation and optimization across diverse hardware devices. In the meanwhile, the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning workloads. This paper combines the trends in these two directions. Specifically, we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as Sunway. In addition, we leverage the architecture features during the compilation such as core group for massive parallelism, DMA for high bandwidth memory transfer and local device memory for data locality, in order to generate efficient codes for deep learning workloads on Sunway. The experiment results show that the codes generated by swTVM achieves 1.79× on average compared to the state-of-the-art deep learning framework on Sunway, across six representative benchmarks. This work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in mind. We believe this work will encourage more people to embrace the power of deep learning and Sunway many-core processor. Copyright © 2019, The Authors. All rights reserved.

关键词： Program compilers

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Many cooks improve the broth: Developing an inter-institutional, online, bachelor of science degree in Information Technology 03

Many cooks improve the broth: Developing an inter-institutio...

引用

4th Conference on Information Technology Curriculum, CITC4 2003

作者： Dehoney, Joanne Booth, Larry Lau, Kam Fui Reichgelt, Han Rutherfoord, Rebecca H. Stewart, Jeff Collaborative Development Consultant Advanced Learning Technologies University System of Georgia Gwinnett University Center 1000 University Center Ln. Bldg B LawrencevilleGA30043 United States IT Department Head College of Information and Mathematical Sciences Clayton College and State University MorrowGA30260 United States School of Computing Armstrong Atlantic State University 11935 Abercorn Street SavannahGA31419 United States Department of Information Technology Georgia Southern University StatesboroGA30461 United States Department Information Technology Southern Polytechnic State Univ. 1100 S. Marietta Parkway MariettaGA30060 United States Division of Information Technology Macon State College 100 College Station Dr. MaconGA31206 United States

ISBN: (纸本)1581137702

Five state colleges and universities in the University of Georgia System are collaborating to develop an online B.S. IT degree, slated to open for enrollment in Fall 2004. The participating institutions range in size and mission from large regional universities to regional colleges. The process of jointly designing a degree to be offered either wholly or substantially online for a non-traditional audience has produced several noteworthy intermediate outcomes. The first peripheral but important outcome is the benefit of collaborative self-study, which has already affected participating programs. Second, online BSIT planning has informed the definition of state-level course requirements for Associate degree level concentrations in Information Technology. In terms of the program itself, intermediate outcomes include a curriculum developed by consensus in reference to emerging accreditation guidelines, closely examined program and course prerequisites, and a process for jointly planning, reviewing and certifying courses. This paper first describes the project's context, background and the needs assessment, then briefly describes the technological and administrative infrastructure required to deliver the degree collaboratively and at a distance. We focus on the program's impact to this point, curricular structure and rationale, and conclude with our expectations for the project's future. Copyright 2003 ACM.

关键词： E-learning

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Nonstoichiometric Mn-doped ZnO magic nanoclusters and their composite structures from ab initio calculations

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Physical Review B 2012年第20期86卷 205320-205320页

作者： Sachin P. Nanavati Vijayaraghavan Sundararajan Shailaja Mahamuni S. V. Ghaisas Vijay Kumar Centre for Development of Advanced Computing (C-DAC) Pune University Campus Pune–411 007 India Department of Electronic Science University of Pune Pune–411 007 India Department of Physics University of Pune Pune–411 007 India Dr. Vijay Kumar Foundation 1969 Sector 4 Gurgaon–122 001 India Center for Informatics School of Natural Sciences Shiv Nadar University Chithera Gautum Budh Nagar–203 207 Uttar Pradesh India

Undoped cages of (ZnO)n nanoclusters are magic with n = 12 and 34. However with Mn doping, our ab initio calculations show that O rich, nonstoichiometric Zn12MnO15 and Zn34MnO37 nanoclusters obtained from n = 13 and 35, become magic with 1μB magnetic moment. The Mn-doped nanoclusters can also be viewed as composite structures where a MnOx species (x = 1–4) is attached to (ZnO)n (n = 12 and 34) cages. Mn atoms can exist in a high oxidation state in these nanoclusters, with the highest binding energy for x = 3. Further replacement of Mn by Cr leads to a neutral, nonmagnetic Zn12CrO15 nanocluster with a large highest occupied molecular orbital and lowest unoccupied molecular orbital gap of 2.24 eV. These results provide new ground to understand doped nanostructures of ZnO and may also shed light on magnetism in Mn-doped ZnO thin films.

关键词： MANGANESE ZINC oxide NANOSTRUCTURES COMPOSITE materials MAGNETIC moments

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The first ICB* competition on iris recognition

The first ICB* competition on iris recognition

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IEEE International Joint Conference on Biometrics (IJCB)

作者： Man Zhang Jing Liu Zhenan Sun Tieniu Tan Wu Su Fernando Alonso-Fernandez Valérian Némesin Nadia Othman Koichi Noda Peihua Li Edmundo Hoyle Akanksha Joshi Center for Research on Intelligent Perception and Computing Institute of Automation Chinese Academy of Sciences (CN) Department of Automation University of Science and Technology of China (CN) Zhuhai YiSheng Electronics Technology Co Ltd (CN) Halmstad University (SE) Centrale Marseille Institut Fresnel (UMR 7249) (FR) CNRS Télécom SudParis Nihon System Laboratory. Ltd (JP) School of Information and Communication Engineering Dalian University of Technology (CN) University Federal of Rio de Janeiro (BR) Centre for Development of Advanced Computing (IN)

Iris recognition becomes an important technology in our society. Visual patterns of human iris provide rich texture information for personal identification. However, it is greatly challenging to match intra-class iris images with large variations in unconstrained environments because of noises, illumination variation, heterogeneity and so on. To track current state-of-the-art algorithms in iris recognition, we organized the first ICB* Competition on Iris Recognition in 2013 (or ICIR2013 shortly). In this competition, 8 participants from 6 countries submitted 13 algorithms totally. All the algorithms were trained on a public database (e.g. CASIA-Iris-Thousand [3]) and evaluated on an unpublished database. The testing results in terms of False Non-match Rate (FNMR) when False Match Rate (FMR) is 0.0001 are taken to rank the submitted algorithms.

关键词： Iris recognition Databases Image segmentation Magnetic resonance Testing Image edge detection Noise

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Coherent H ∞ control for Markovian jump linear quantum systems

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IFAC-PapersOnLine 2020年第2期53卷 269-274页

作者： Yanan Liu Daoyi Dong Ian R. Petersen Qing Gao Steven X. Ding Hidehiro Yonezawa School of Engineering and Information Technology University of New South Wales Canberra ACT 2600 Australia Center for Quantum Computation and Communication Technology Australian Research Council Canberra ACT 2600 Australia Institute for Automatic Control and Complex Systems (AKS) University of Duisburg-Essen. 47057 Duisburg Germany Research School of Electrical Energy and Materials Engineering The Australian National University Canberra ACT 2601 Australia School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment Beijing and also with Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing 100191 China

The purpose of this paper is to design a coherent feedback controller for a Markovian jump linear quantum system suffering from a fault signal. The control objective is to bound the effect of the disturbance input on the output for the time-varying quantum system. We prove the relation between the H ∞ control problem, the dissipation properties, and the solutions of Riccati differential equations, by which the H ∞ controller of the Markovian jump linear quantum system is given by the solutions of Linear Matrix Inequalities (LMIs).

关键词： Coherent quantum feedback H∞ control fault-tolerant control Markovian jump linear quantum systems

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Uncertainty-Aware Relational Graph Neural Network for Few-Shot Knowledge Graph Completion

arXiv

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arXiv 2024年

作者： Li, Qian Guo, Shu Chen, Yingjia Ji, Cheng Sheng, Jiawei Li, Jianxin Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100083 China The State Key Laboratory of Software Development Environment Beihang University Beijing100083 China National Computer Network Emergency Response Technical Team Coordination Center of China Beijing100083 China School of Mathematics Edinburgh University Edinburgh United Kingdom Institute of Information Engineering Chinese Academy of Sciences Beijing100083 China School of Cyber Security University of Chinese Academy of Sciences Beijing100083 China

Few-shot knowledge graph completion (FKGC) aims to query the unseen facts of a relation given its few-shot reference entity pairs. The side effect of noises due to the uncertainty of entities and triples may limit the few-shot learning, but existing FKGC works neglect such uncertainty, which leads them more susceptible to limited reference samples with noises. In this paper, we propose a novel uncertainty-aware few-shot KG completion framework (UFKGC) to model uncertainty for a better understanding of the limited data by learning representations under Gaussian distribution. Uncertainty representation is first designed for estimating the uncertainty scope of the entity pairs after transferring feature representations into a Gaussian distribution. Further, to better integrate the neighbors with uncertainty characteristics for entity features, we design an uncertainty-aware relational graph neural network (UR-GNN) to conduct convolution operations between the Gaussian distributions. Then, multiple random samplings are conducted for reference triples within the Gaussian distribution to generate smooth reference representations during the optimization. The final completion score for each query instance is measured by the designed uncertainty optimization to make our approach more robust to the noises in few-shot scenarios. Experimental results show that our approach achieves excellent performance on two benchmark datasets compared to its competitors. Copyright © 2024, The Authors. All rights reserved.

关键词： Graph neural networks

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MICROSIM: A high performance phase-field solver based on CPU and GPU implementations

arXiv

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arXiv 2024年

作者： Dutta, Tanmay Mohan, Dasari Shenoy, Saurav Attar, Nasir Kalokhe, Abhikshek Sagar, Ajay Bhure, Swapnil Pradhan, Swaroop S. Praharaj, Jitendriya Mridha, Subham Kushwaha, Anshika Shah, Vaishali Gururajan, M.P. Shenoi, V. Venkatesh Phanikumar, Gandham Bhattacharyya, Saswata Choudhury, Abhik Department of Materials Engineering Indian Institute of Science Karnataka Bangalore560012 India Department of Metallurgical and Materials Engineering IIT Madras Tamil Nadu Chennai600036 India Department of Materials Science and Metallurgical Engineering IIT Hyderabad Telangana Hyderabad502284 India Center for development of Advanced Computing Pune University Campus Maharashtra Pune411007 India Department of Metallurgical Engineering and Materials Science IIT Bombay Powai Maharashtra Mumbai400076 India Department of Scientific Computing Modeling and Simulation Savitribai Phule Pune University Maharashtra Pune411007 India

The phase-field method has become a useful tool for the simulation of classical metallurgical phase transformations as well as other phenomena related to materials science. The thermodynamic consistency that forms the basis of these formulations lends to its strong predictive capabilities and utility. However, a strong impediment to the usage of the method for typical applied problems of industrial and academic relevance is the significant overhead with regard to the code development and know-how required for quantitative model formulations. In this paper, we report the development of an open-source phase-field software stack that contains generic formulations for the simulation of multi-phase and multi-component phase transformations. The solvers incorporate thermodynamic coupling that allows the realization of simulations with real alloys in scenarios directly relevant to the materials industry. Further, the solvers utilize parallelization strategies using either multiple CPUs or GPUs to provide cross-platform portability and usability on available supercomputing machines. Finally, the solver stack also contains a graphical user interface to gradually introduce the usage of the software. The user interface also provides a collection of post-processing tools that allow the estimation of useful metrics related to microstructural evolution. © 2024, CC BY-NC-SA.

关键词： Technology transfer

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