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Solution-Processable Pure-Red Multiple Resonance-induced Thermally Activated Delayed Fluorescence Emitter for Organic Light-Emitting Diode with External Quantum Efficiency over 20 %

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Angewandte Chemie 2022年第7期135卷

作者： Xinliang Cai Dr. Yincai Xu Yue Pan Linjie Li Yexuan Pu Dr. Xuming Zhuang Prof. Chenglong Li Prof. Yue Wang State Key Laboratory of Supramolecular Structure and Materials College of Chemistry Jilin University Changchun 130012 P. R. China Contribution: Data curation (lead) Formal analysis (equal) Supervision (equal) Validation (equal) Writing - original draft (lead) Writing - review & editing (equal) Contribution: Conceptualization (equal) Methodology (equal) Writing - original draft (equal) Key Laboratory for Molecular Enzymology and Engineering of Ministry of Education School of Life Science Jilin University Changchun 130012 P. R. China Contribution: Formal analysis (equal) Methodology (equal) Software (equal) Contribution: Formal analysis (equal) Methodology (equal) Jihua Laboratory 28 Huandao South Road Foshan 528200 Guangdong Province P. R. China Contribution: Data curation (equal) Methodology (lead) Software (equal) Visualization (equal) Chongqing Research Institute Jilin University Chongqing 401120 P. R. China Contribution: Conceptualization (lead) Formal analysis (equal) Methodology (equal) Supervision (equal) Visualization (equal) Writing - original draft (equal) Writing - review & editing (equal) Jihua Hengye Electronic Materials CO. LTD. Foshan 528200 Guangdong Province P. R. China Contribution: Supervision (equal) Visualization (equal) Writing - original draft (supporting)

Developing solution-processable red organic light-emitting diodes (OLEDs) with high color purity and efficiency based on multiple resonance thermally activated delayed fluorescence (MR-TADF) is a formidable challenge. Herein, by introducing auxiliary electron donor and acceptor moieties into the highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO) distributed positions of multiple resonance skeleton simultaneously, an effective strategy to obtain red MR-TADF emitters was represented. The proof-of-the-concept molecule BN-R exhibits a narrowband pure-red emission at 624 nm, with a high luminous efficiency of 94 % and a narrow bandwidth of 46 nm. Notably, the fabricated solution-processable pure-red OLED based on BN-R exhibits a state-of-the-art external quantum efficiency over 20 % with the Commission Internationale de I’Éclairage coordinates of (0.663, 0.337) and a long operational lifetime (LT 50 ) of 1088 hours at an initial luminance of 1000 cd m −2 .

关键词： Multiple Resonance Narrowband Emission Organic Light-Emitting Diodes Solution-Processed Thermally Activated Delayed fluorescence

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τ-FPL: Tolerance-constrained learning in linear time

arXiv

引用

arXiv 2018年

作者： Zhang, Ao Li, Nan Pu, Jian Wang, Jun Yan, Junchi Zha, Hongyuan School of Computer Science and Software Engineering East China Normal University Shanghai China Institute of Data Science and Technologies Alibaba Group Hangzhou China IBM Research - China Shanghai China College of Computing Georgia Institute of Technology AtlantaGA United States

Learning a classifier with control on the false-positive rate plays a critical role in many machine learning applications. Existing approaches either introduce prior knowledge dependent label cost or tune parameters based on traditional classifiers, which lack consistency in methodology because they do not strictly adhere to the false-positive rate constraint. In this paper, we propose a novel scoring-thresholding approach, τ -False Positive Learning (τ - FPL) to address this problem. We show the scoring problem which takes the false-positive rate tolerance into accounts can be efficiently solved in linear time, also an out-of-bootstrap thresholding method can transform the learned ranking function into a low false-positive classifier. Both theoretical analysis and experimental results show superior performance of the proposed τ -FPL over existing approaches. Copyright © 2018, The Authors. All rights reserved.

关键词： Mathematical transformations

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Intentional control of type I error over unconscious data distortion: A neyman-pearson approach to text classification

arXiv

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arXiv 2018年

作者： Xia, Lucy Zhao, Richard Wu, Yanhui Tong, Xin Department of Statistics Stanford University Department of Computer Science and Software Engineering The Behrend College Pennsylvania State University Department of Economics and Finance Marshall School of Business University of Southern California Department of Data Sciences and Operations Marshall School of Business University of Southern California

Digital texts have become an increasingly important source of data for social studies. However, textual data from open platforms are vulnerable to manipulation (e.g., censorship and information inflation), often leading to bias in subsequent empirical analysis. This paper investigates the problem of data distortion in text classification when controlling type I error (a relevant textual message is classified as irrelevant) is the priority. The default classical classification paradigm that minimizes the overall classification error can yield an undesirably large type I error, and data distortion exacerbates this situation. As a solution, we propose the Neyman-Pearson (NP) classification paradigm which minimizes type II error under a user-specified type I error constraint. Theoretically, we show that while the classical oracle (i.e., optimal classifier) cannot be recovered under unknown data distortion even if one has the entire post-distortion population, the NP oracle is unaffected by data distortion and can be recovered under the same condition. Empirically, we illustrate the advantage of NP classification methods in a case study that classifies posts about strikes and corruption published on a leading Chinese blogging platform. Copyright © 2018, The Authors. All rights reserved.

关键词： Social networking (online)

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Global Pinning Synchronization with PI Controller in General Complex Directed Networks

Global Pinning Synchronization with PI Controller in General...

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第37届中国控制会议

作者： Peng Liu Haibo Gu Jinhu Lü Yu Kang Department of Automation University of Science and Technology of China LSC Academy of Mathematics and Systems ScienceChinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environmentand Beijing Advanced Innovation Center for Big Data and Brain Machine IntelligenceBeihang University

Global pinning synchronization in complex networks has been extensively studied in the last decades due to its potential *** question is how to design an available controller to achieve global synchronization when the network is *** we all know,the classical PI controller is most widely and successfully used in engineering systems with nonlinear ***,the global synchronization with PI controller in general complex directed networks still remain *** this paper we will theoretically show that the global synchronization of some directed networks can also be ensured by designing an appropriate PI controller and pioneering some selected nodes,then a simple numerical example will also be given to verify our main results.

关键词： Directed network Pining synchronization PI controller Lyapunov method

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Distributed PI Control for Synchronization in Directed Strongly Connected Complex Dynamical Networks

Distributed PI Control for Synchronization in Directed Stron...

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第37届中国控制会议

作者： Haibo Gu Peng Liu Xiong Wang Jinhu L LSC Academy of Mathematics and Systems Science Chinese Academy of Sciences School of Mathematical Sciences University of Chinese Academy of Sciences Department of Automation University of Science and Technology of China School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence Beihang University

Synchronization of directed complex networks has been extensively studied in the previous two decades due to its potential applications in the real world practices. To reveal and analyze the inherent mechanism of global synchronization in the complex networks with directed topologies, this paper attempts to developing a novel synchronization approach by using algebraic connectivity and PI control protocols. First, we studied the distributed PI control for synchronization in directed strongly connected networks and obtained some sufficient conditions to guarantee the networks reach global ***, a numerical example is given to verify the effectiveness of the proposed theoretical results.

关键词： Synchronization distributed PI control strongly connected network network control systems

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Multi-pseudo regularized label for generated data in person re-identification

arXiv

引用

arXiv 2018年

作者： Huang, Yan Xu, Jingsong Wu, Qiang Zheng, Zhedong Zhang, Zhaoxiang Zhang, Jian School of Electrical and Data Engineering University of Technology Sydney Australia School of Software University of Technology Sydney Australia Research Center for Brain-Inspired Intelligence CAS Center for Excellence in Brain Science and Intelligence Technology Institute of Automation Chinese Academy of Sciences Beijing100190 China

Sufficient training data normally is required to train deeply learned models. However, due to the expensive manual process for labelling large number of images (i.e., annotation), the amount of available training data (i.e., real data) is always limited. To produce more data for training a deep network, Generative Adversarial Network (GAN) can be used to generate artificial sample data (i.e., generated data). However, the generated data usually does not have annotation labels. To solve this problem, in this paper, we propose a virtual label called Multi-pseudo Regularized Label (MpRL) and assign it to the generated data. With MpRL, the generated data will be used as the supplementary of real training data to train a deep neural network in a semi-supervised learning fashion. To build the corresponding relationship between the real data and generated data, MpRL assigns each generated data a proper virtual label which reflects the likelihood of the affiliation of the generated data to pre-defined training classes in the real data domain. Unlike the traditional label which usually is a single integral number, the virtual label proposed in this work is a set of weight-based values each individual of which is a number in (0,1] called multi-pseudo label and reflects the degree of relation between each generated data to every pre-defined class of real data. A comprehensive evaluation is carried out by adopting two state-of-the-art convolutional neural networks (CNNs) in our experiments to verify the effectiveness of MpRL. Experiments demonstrate that by assigning MpRL to generated data, we can further improve the person re-ID performance on five re-ID datasets, i.e., Market-1501, DukeMTMC-reID, CUHK03, VIPeR, and CUHK01. The proposed method obtains +6.29%, +6.30%, +5.58%, +5.84%, and +3.48% improvements in rank-1 accuracy over a strong CNN baseline on the five datasets respectively, and outperforms state-of-the-art methods. Copyright © 2018, The Authors. All rights reserved

关键词： Deep neural networks

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A Novel Personalized Recommendation Algorithm Based on Trust Relevancy Degree

A Novel Personalized Recommendation Algorithm Based on Trust...

引用

IEEE International Symposium on Dependable, Autonomic and Secure Computing (DASC)

作者： Weimin Li Heng Zhu Xiaokang Zhou Shohei Shimizu Mingjun Xin Qun Jin School of Computer Engineering and Technology Shanghai University Shanghai China Faculty of Data Science Shiga University Hikone Japan Software Evaluating and Testing Shanghai Key Laboratory of Computer Shanghai China Faculty of Human Sciences Waseda University Japan

ISBN: (纸本)9781538675199

The rapid development of the Internet and ecommerce has brought a lot of convenience to people's life. Personalized recommendation technology provides users with services that they may be interested according to users' information such as personal characteristics and historical behaviors. The research of personalized recommendation has been a hot point of data mining and social networks. In this paper, we focus on resolving the problem of data sparsity based on users' rating data and social network information, introduce a set of new measures for social trust and propose a novel personalized recommendation algorithm based on matrix factorization combining trust relevancy. Our experiments were performed on the Dianping datasets. The results show that our algorithm outperforms traditional approaches in terms of accuracy and stability.

关键词： Social network services Collaboration Filtering Prediction algorithms Training data science Internet

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Cryptanalysis of novel extended multivariate public key cryptosystem with invertible cycle

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International Journal of Network Security 2018年第3期20卷 509-514页

作者： Lu, Gang Xue, Linyuan Nie, Xuyun Qin, Zhiguang School of Information and Software Engineering University of Electronic Science and Technology of China Section 2 North Jianshe Road Chengdu610054 China State Key Laboratory of Information Security Institute of Information Engineering China Network and Data Security Key Laboratory of Sichuan Province China

In 2016, Qiao et al. proposed a novel extended multivariate public key cryptosystem (EMC) to enhance the security of multivariate public key cryptosystem. They applied it on Matsumoto-Imai (MI) encryption scheme and claimed that the enhanced MI scheme can be secure against Linearization Equation (LE) attack. Through analysis, we found that the enhanced MI scheme satisfied Quadratization Equations (QE). After finding all the quadratization equations, we can recover the plaintext corresponding to a valid ciphertext of the enhanced MI scheme. © International Journal of Network Security.

关键词： Public key cryptography

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A parallel random forest algorithm for big data in a spark cloud computing environment

arXiv

引用

arXiv 2018年

作者： Chen, Jianguo Li, Kenli Tang, Zhuo Bilal, Kashif Yu, Shui Weng, Chuliang Li, Keqin College of Computer Science and Electronic Engineering Hunan University National Supercomputing Center in Changsha Changsha410082 China Comsats Institute of Information Technology Islamabad45550 Pakistan School of Information Technology Deakin University MelbourneVIC3216 Australia School of Computer Science and Software Engineering Institute for Data Science and Engineering East China Normal University Shanghai200241 China Department of Computer Science State University of New York New PaltzNY12561 United States

With the emergence of the big data age, the issue of how to obtain valuable knowledge from a dataset efficiently and accurately has attracted increasingly attention from both academia and industry. This paper presents a Parallel Random Forest (PRF) algorithm for big data on the Apache Spark platform. The PRF algorithm is optimized based on a hybrid approach combining data-parallel and task-parallel optimization. From the perspective of data-parallel optimization, a vertical data-partitioning method is performed to reduce the data communication cost effectively, and a data-multiplexing method is performed is performed to allow the training dataset to be reused and diminish the volume of data. From the perspective of task-parallel optimization, a dual parallel approach is carried out in the training process of RF, and a task Directed Acyclic Graph (DAG) is created according to the parallel training process of PRF and the dependence of the Resilient Distributed datasets (RDD) objects. Then, different task schedulers are invoked for the tasks in the DAG. Moreover, to improve the algorithm's accuracy for large, high-dimensional, and noisy data, we perform a dimension-reduction approach in the training process and a weighted voting approach in the prediction process prior to parallelization. Extensive experimental results indicate the superiority and notable advantages of the PRF algorithm over the relevant algorithms implemented by Spark MLlib and other studies in terms of the classification accuracy, performance, and scalability. Copyright © 2018, The Authors. All rights reserved.

关键词： Cloud computing

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Conferring BiVO4Nanorods with Oxygen Vacancies to Realize Enhanced Sonodynamic Cancer Therapy

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Angewandte Chemie 2022年第44期134卷

作者： Dr. Zhuang Yang Dr. Meng Yuan Dr. Bin Liu Dr. Wenying Zhang Dr. Aziz Maleki Prof. Baolin Guo Prof. Ping'an Ma Prof. Ziyong Cheng Prof. Jun Lin State Key Laboratory of Rare Earth Resource Utilization Changchun Institute of Applied Chemistry Changchun 130022 P. R. China School of Applied Chemistry and Engineering University of Science and Technology of China Hefei 230026 P. R. China Contribution: Investigation (lead) Methodology (lead) Resources (lead) Supervision (lead) Writing - original draft (lead) Writing - review & editing (lead) Contribution: Conceptualization (equal) Investigation (equal) Software (lead) Contribution: Formal analysis (supporting) Funding acquisition (supporting) Methodology (supporting) Contribution: Data curation (supporting) Project administration (supporting) Resources (supporting) Zanjan Pharmaceutical Nanotechnology Research Center (ZPNRC) and Department of Pharmaceutical Nanotechnology School of Pharmacy Zanjan University of Medical Sciences Zanjan 45139-56184 Iran Contribution: Methodology (supporting) Resources (supporting) State Key Laboratory for Mechanical Behavior of Materials and Frontier Institute of Science and Technology and Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research College of Stomatology Xi'an Jiaotong University Xi'an 710049 P. R. China Contribution: Investigation (supporting) Validation (supporting) Contribution: Formal analysis (supporting) Software (supporting) Visualization (supporting) Guangdong Provincial Key Laboratory of Research and Development of Natural Drugs School of Pharmacy Guangdong Medical University Guangdong Medical University Key Laboratory of Research and Development of New Medical Materials Dongguan 523808 P. R. China Contribution: Validation (lead) Visualization (lead) Writing - original draft (lead) Writing - review & editing (lead) Contribution: Resources (lead) Visualization (lead) Writing - review & editing (lead)

Owing to the high depth of tissue penetration, non-invasiveness, and controllability, ultrasound (US)-mediated sonodynamic therapy (SDT) has shown broad application prospects for tumor treatment. However, the electron-hole separation inefficiency of sonosensitizers and the tumor hypoxia remain two major challenges limiting the effect of SDT. Here, ultrafine photoetched bismuth vanadate (BiVO 4 ) nanorods modified with DSPE-PEG 2000 (PEBVO@PEG NRs) were fabricated to achieve in situ self-supply of oxygen (O 2 ) and reactive oxygen species (ROS) for hypoxic tumor therapy. The photoetching approach could enhance the charge separation by inducing enriched oxygen vacancies on the surface of BiVO 4 , thereby improving the generation efficiency of ROS and O 2 . The PEBVO@PEG overcome the main obstacles of traditional sonosensitizers in the SDT process and show promising sonodynamic therapeutic effects, thus providing new strategies for improving the performance of sonosensitizer and hypoxic tumor elimination.

关键词： Bismuth Vanadate Sonodynamic Therapy Sonosensitizers Surface Oxygen Vacancies Ultrasound

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