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Current progress in developing metal oxide nanoarrays-based photoanodes for photoelectrochemical water splitting

science Bulletin 2019年第18期64卷 1348-1380页

作者： Yongcai Qiu Zhenghui Pan Haining Chen Daiqi Ye Lin Guo Zhiyong Fan Shihe Yang Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control School of Environment and EnergySouth China University of TechnologyGuangzhou 510006China State Key Laboratory of Luminescent Materials and Devices South China University of TechnologyGuangzhou 510640China Department of Materials Science and Engineering National University of SingaporeSingapore 117574Singapore School of Materials Science and Engineering Beihang UniversityBeijing 100191China School of Chemistry and Environment Beihang UniversityBeijing 100191China Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyHong KongChina Department of Chemistry The Hong Kong University of Science and TechnologyHong KongChina Guangdong Key Lab of Nano-Micro Material Research School of Chemical Biology and Biotechnology Shenzhen Graduate SchoolPeking UniversityShenzhen 518055China

Solar energy driven photoelectrochemical(PEC) water splitting is a clean and powerful approach for renewable hydrogen production. The design and construction of metal oxide based nanoarray photoanodes is one of the promising strategies to make the continuous breakthroughs in solar to hydrogen conversion efficiency of PEC cells owing to their owned several advantages including enhanced reactive surface at the electrode/electrolyte interface, improved light absorption capability, increased charge separation efficiency and direct electron transport pathways. In this Review, we first introduce the structure,work principle and their relevant efficiency calculations of a PEC cell. We then give a summary of the state-of the-art research in the preparation strategies and growth mechanism for the metal oxide based nanoarrays, and some details about the performances of metal oxide based nanoarray photoanodes for PEC water splitting. Finally, we discuss key aspects which should be addressed in continued work on realizing high-efficiency metal oxide based nanoarray photoanodes for PEC solar water splitting systems.

关键词： Photoelectrochemical water splitting Metal oxide based nanoarray photoanodes Preparation strategies and growth mechanism

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Joint Observation of the Galactic Center with MAGIC and CTA-LST-1 38

Joint Observation of the Galactic Center with MAGIC and CTA-...

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38th International Cosmic Ray Conference, ICRC 2023

作者： Abe, Shotaro Berti, Alessio Di Pierro, Federico López-Coto, Rubén Moralejo, Abelardo Ohtani, Yoshiki Sitarek, Julian Strzys, Marcel Suda, Yusuke Vovk, Ievgen Abe, H. Abe, K. Abe, S. Abhir, J. Acciari, V.A. Aguasca-Cabot, A. Agudo, I. Alvarez Crespo, N. Aniello, T. Ansoldi, S. Antonelli, L.A. Aramo, C. Arbet-Engels, A. Cornelia, A. Artero, M. Asano, K. Aubert, P. Baack, D. Babić, A. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Baxter, J. Becerra González, J. Bednarek, W. Bernardini, E. Bernardos, M.I. Bernete Medrano, J. Berti, A. Besenrieder, J. Bhattacharjee, P. Biederbeck, N. Bigongiari, C. Biland, A. Bissaldi, E. Blanch, O. Bonnoli, G. Bordas, P. Bošnjak, Ž. Bulgarelli, A. Burelli, I. Burmistrov, L. Buscemi, M. Busetto, G. Campoy-Ordaz, A. Cardillo, M. Caroff, S. Carosi, A. Carosi, R. Carrasco, M.S. Carretero-Castrillo, M. Cassol, F. Castro-Tirado, A.J. Cauz, D. Cerasole, D. Ceribella, G. Chai, Y. Cheng, K. Chiavassa, A. Chikawa, M. Chilingarian, A. Chytka, L. Cifuentes, A. Cikota, S. Colombo, E. Contreras, J.L. Cortina, J. Costantini, H. Covino, S. D’Amico, G. Dalchenko, M. D’Elia, V. Da Vela, P. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Lotto, B. De Lucia, M. de Menezes, R. Del Peral, L. Deleglise, G. Delfino, M. Delgado, C. Delgado Mengual, J. della Volpe, D. Dellaiera, M. Del Popolo, A. Depaoli, D. Di Piano, A. Di Pierro, F. Di Pilato, A. Di Tria, R. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Eisenberger, L. Elsässer, D. Emery, G. Escudero, J. Fallah Ramazani, V. Fariña, L. Fattorini, A. Ferrara, G. Ferrarotto, F. Fiasson, A. Foffano, L. Font, L. Freixas Coromina, L. Fröse, S. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Garczarczyk, M. Gasbarra, C. Gasparrini, D. Gasparyan, S. Gaug, M. Geyer, D. Giesbrecht Paiva, J. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Grau, R. Green, J. Green, D. Gunji, S. Günther, P. Hackfeld, J. Hadasch, D. Hahn, A. Institute for Cosmic Ray Research Kashiwa-no-ha 5-1-5 Kashiwa-shi Chiba Japan Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany INFN Sezione di Torino Via P. Giuria 1 Torino10125 Italy Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain The Barcelona Institute of Science and Technology Campus UAB Bellaterra Barcelona08193 Spain Faculty of Physics and Applied Informatics University of Lodz ul. Pomorska 149-153 Lodz90-236 Poland Physics Program Graduate School of Advanced Science and Engineering Hiroshima University Hiroshima739-8526 Japan Institute for Cosmic Ray Research University of Tokyo Japan Department of Physics Tokai University Japan ETH Zürich Switzerland Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Spain Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Spain EMFTEL department IPARCOS Universidad Complutense de Madrid Spain Italy INFN Sezione di Trieste Università degli Studi di Udine Italy Italy INAF Osservatorio Astronomico di Roma Italy INFN Sezione di Napoli Italy INFN Sezione di Padova Università degli Studi di Padova Italy LAPP Univ. Grenoble Alpes Univ. Savoie Mont Blanc CNRS-IN2P3 Annecy France Department of Physics TU Dortmund University Germany Croatia Universität Hamburg Institut für Experimentalphysik Germany Graduate School of Science University of Tokyo Japan Universidad del Azuay Ecuador INAF Osservatorio di Astrofisica e Scienza dello spazio di Bologna Italy Centro Brasileiro de Pesquisas Físicas Brazil CIEMAT Spain INFN Sezione di Bari Politecnico di Bari Italy INAF Osservatorio Astronomico di Brera Italy University of Geneva Département de physique nucléaire et corpusculaire Switzerland INFN Sezione di Catania Italy Departament de Física CERES-IEEC Universitat Autónoma de Barcelona Spain Italy Università di Pisa INFN Pisa Italy Aix Mars

MAGIC is a system of two Imaging Atmospheric Cherenkov Telescopes (IACTs), designed to detect very-high-energy gamma rays, and is operating in stereoscopic mode since 2009 at the Observatorio del Roque de Los Muchachos in La Palma, Spain. In 2018, the prototype IACT of the Large-Sized Telescope (LST-1) for the Cherenkov Telescope Array, a next-generation ground-based gamma-ray observatory, was inaugurated at the same site, at a distance of approximately 100 meters from the MAGIC telescopes. Using joint observations between MAGIC and LST-1, we developed a dedicated analysis pipeline and established the threefold telescope system via software, achieving the highest sensitivity in the northern hemisphere. Based on this enhanced performance, MAGIC and LST-1 have been jointly and regularly observing the Galactic Center, a region of paramount importance and complexity for IACTs. In particular, the gamma-ray emission from the dynamical center of the Milky Way is under debate. Although previous measurements suggested that a supermassive black hole Sagittarius A* plays a primary role, its radiation mechanism remains unclear, mainly due to limited angular resolution and sensitivity. The enhanced sensitivity in our novel approach is thus expected to provide new insights into the question. We here present the current status of the data analysis for the Galactic Center joint MAGIC and LST-1 observations. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Cosmology

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Hybrid Intelligent-Annotation Organ Segmentation on Medical Datasets

Hybrid Intelligent-Annotation Organ Segmentation on Medical ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Tao Peng Jing Zhao Yidong Gu Gongye Di Lei Zhang Jing Cai School of Future Science and Engineering Soochow University Suzhou China Department of Radiation Oncology UT Southwestern Medical Center Dallas TX USA Department of Ultrasound Tsinghua University Affiliated Beijing Tsinghua Changgung Hospital Beijing China Department of Medical Ultrasound Suzhou Municipal Hospital The Affiliated Suzhou Hospital of Nanjing Medical University Suzhou Jiangsu China Department of Ultrasonic The Affiliated Taizhou People's Hospital of Nanjing Medical University Taizhou China Graduate Program of Medical Physics and Data Science Research Center Duke Kunshan University Kunshan Jiangsu China Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong China

Ultrasound image segmentation is crucial for early disease detection and treatment planning but remains a challenging task due to the low contrast of organ boundaries and varying image quality. Current methods often require manual intervention or have limited accuracy. In this paper, we propose a novel hybrid framework that combines an automatic option polygon segment (AOPS) algorithm and a distributed- and memory-based evolution (DME) algorithm for precise ultrasound organ segmentation. Our pipeline consists of two cascaded stages: (1) a coarse segmentation step using the AOPS algorithm, which determines the number of vertices/clusters without human intervention, and (2) a refinement step using the DME algorithm to hunt for the optimal neural network, which is then used to represent a smooth, explainable mathematical expression of the organ boundary. We employ the fractional backpropagation learning network with L2 regularization (FBLN) for training and use the scaled exponential linear unit (SELU) activation function to address the vanishing gradient problem. This is a new attempt such a hybrid framework is applied to ultrasound organ segmentation tasks, and it demonstrates significant contributions in terms of accuracy, smoothness, and computational efficiency.

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Recent advances in molecularly imprinted polymers toward biomedical healthcare devices

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Biosensors and Bioelectronics 2025年 287卷 117637页

作者： Seo, Youngjun Kim, Yonghwan Kim, Jaeheung Jung, Hyo Gi Jang, Jae Won Kim, Hyunji Hwang, Kyo Seon Lee, Dongtak Lee, Sang Won Lee, Jeong Hoon Yoon, Dae Sung School of Biomedical Engineering Korea University Seoul02841 Korea Republic of Interdisciplinary Program in Precision Public Health Korea University Seoul02841 Korea Republic of Department of Clinical Pharmacology and Therapeutics College of Medicine Kyung Hee University Seoul02447 Korea Republic of Department of Bioengineering & Nano-bioengineering Research Center for Bio Materials and Process Development Incheon National University Incheon22012 Korea Republic of Division of Bioengineering Incheon National University Incheon22012 Korea Republic of Terasaki Institute for Biomedical Innovation Los AngelesCA90064 United States KU-KIST Graduate School of Converging Science and Technology Korea University Seoul02841 Korea Republic of Department of Integrative Energy Engineering College of Engineering Korea University Seoul02841 Korea Republic of Astrion Inc Seoul02841 Korea Republic of

Following the increase in the global aging population, the importance of monitoring various disease-related biomarkers at an early stage has increased to ensure the health of the elderly. In an aging society, point-of-care (POC) systems are needed to care for elderly people who have physical and mental disorders. In light of the increasing prominence of POC systems, there is a growing effort to address the limitations associated with conventional receptors in wearable devices by substituting them with molecularly imprinted polymer (MIP). MIPs are well-known synthetic receptors engineered with specific binding cavities based on the "lock and key" principle. They could be synthesized in various configurations depending on specific types of monomers and templates. Compared to conventional receptors such as antibodies and aptamers, MIPs exhibit outstanding advantages, including good stability, cost-effectiveness, ease of synthesis, reusability, and broad applicability. These advantages have led to their extensive application in biomedical healthcare devices. This review summarizes a comparative analysis of sensors utilized for the detection of disease-specific biomarkers through diverse MIP applications and methodologies. Furthermore, we evaluated recent advancements in the miniaturization of MIPs and their integration with wearable biomedical devices for comprehensive healthcare monitoring applications. Finally, we delineated the existing limitations that need to be surmounted for the effective implementation of MIP-based biomedical devices and outlined future objectives for the enhancement of wearable and wireless biomedical healthcare monitoring devices. © 2025 Elsevier B.V.

关键词： Diseases

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The weak min-max property in Banach spaces

arXiv

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arXiv 2021年

作者： Ouyang, Zhengyong Rasila, Antti Guan, Tiantian School of Mathematics and Big Data Foshan University Foshan Guangdong528000 China Mathematics with Computer Science Program Guangdong Technion-Israel Institute of Technology 241 Daxue Road Shantou Guang-dong515063 China Department of Mathematics Technion-Israel Institute of Technology Haifa32000 Israel

In this paper, we investigate the relationship between the weak minmax property and the diameter uniformity of domains in Banach spaces with dimensions at least 2. As an application, we show that diameter uniform domains are invariant under relatively quasimöbius *** Codes Primary: 30C65, Secondary: 30C20. Copyright © 2021, The Authors. All rights reserved.

关键词： Mapping

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MQA: Answering the Question via Robotic Manipulation

arXiv

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arXiv 2020年

作者： Deng, Yuhong Guo, Di Guo, Xiaofeng Zhang, Naifu Liu, Huaping Sun, Fuchun Department of Computer Science and Technology Tsinghua University China Beijing National Research Center for Information Science and Technology Center of Intelligent Control and Telescience Tsinghua Shenzhen International Graduate School Tsinghua University China

In this paper, we propose a novel task, Manipulation Question Answering (MQA), where the robot performs manipulation actions to change the environment in order to answer a given question. To solve this problem, a framework consisting of a QA module and a manipulation module is proposed. For the QA module, we adopt the method for the Visual Question Answering (VQA) task. For the manipulation module, a Deep Q Network (DQN) model is designed to generate manipulation actions for the robot to interact with the environment. We consider the situation where the robot continuously manipulating objects inside a bin until the answer to the question is found. Besides, a novel dataset that contains a variety of object models, scenarios and corresponding question-answer pairs is established in a simulation environment. Extensive experiments have been conducted to validate the effectiveness of the proposed framework. Copyright © 2020, The Authors. All rights reserved.

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Deep Clustering with LSTM for Vital Signs Separation in Contact-free Heart Rate Estimation

Deep Clustering with LSTM for Vital Signs Separation in Cont...

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IEEE International Conference on Communications (ICC)

作者： Chen Ye Guan Gui Tomoaki Ohtsuki Graduate School of Science and Technology Keio University Yokohama Japan College of Telecommunications and Information Engineering NJUPT Nanjing China Department of Informand Computer Science Keio University Yokohama Japan

ISBN: (数字)9781728150895

ISBN: (纸本)9781728150901

So far, most separation approaches of vital signs such as heartbeat and respiration, are implemented based on linear mixtures. However, some literatures have reported that non-linear mixtures actually occur in the associated applications, e.g., heart rate (HR) estimation with Doppler radar, where the simple linear demixing architecture may limit the effect of source separation. In addition, the human motions during HR measurement further complicate the mixing processes. The issue motivates us to exploit a more suitable separation approach to deal with contact-free HR estimation, considering non-linear mixtures including motions. A semi-supervised deep clustering (DC) is proposed to separate the three mixed sources of heartbeat, respiration, and motions, by segmenting the spectrogram of Doppler signal. First, through training a deep recurrent neural network (RNN) with long short-term memory (LSTM) via heartbeat/respiration-only data, the embeddings to each frame-sample from spectrogram can be acquired, which enables feature optimization in a lower dimensional space. Then, in the test phase, K-means clusters the embeddings associated with each source, to infer the masks used for spectrogram segmentation. The proposed deep clustering has three main strengths: It (i) gets rid of the restriction of mixture class, relying on data mining; (ii) can handle three-source mixtures by training two sorts of source-independent samples; (iii) only requires the mixtures from single-channel. The HR measurement experiments on subjects' sitting still and typing, validate the improvements of accuracy and robustness by our proposal, over some prevailing approaches in signal decomposition or separation.

关键词： Heart beat Estimation Spectrogram Doppler radar Doppler effect Training

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Proving tree algorithms for succinct data structures 10

Proving tree algorithms for succinct data structures

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10th International Conference on Interactive Theorem Proving, ITP 2019

作者： Affeldt, Reynald Garrigue, Jacques Qi, Xuanrui Tanaka, Kazunari National Institute of Advanced Industrial Science and Technology Tsukuba Japan Graduate School of Mathematics Nagoya University Japan Department of Computer Science Tufts University MedfordMA United States

ISBN: (纸本)9783959771221

Succinct data structures give space-efficient representations of large amounts of data without sacrificing performance. They rely on cleverly designed data representations and algorithms. We present here the formalization in Coq/SSReflect of two different tree-based succinct representations and their accompanying algorithms. One is the Level-Order Unary Degree Sequence, which encodes the structure of a tree in breadth-first order as a sequence of bits, where access operations can be defined in terms of Rank and Select, which work in constant time for static bit sequences. The other represents dynamic bit sequences as binary balanced trees, where Rank and Select present a low logarithmic overhead compared to their static versions, and with efficient insertion and deletion. The two can be stacked to provide a dynamic representation of dictionaries for instance. While both representations are well-known, we believe this to be their first formalization and a needed step towards provably-safe implementations of big data. © Reynald Affeldt, Jacques Garrigue, Xuanrui Qi, and Kazunari Tanaka.

关键词： Binary trees

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Quantum Algorithm for Lexicographically Minimal String Rotation

arXiv

引用

arXiv 2020年

作者： Wang, Qisheng Ying, Mingsheng The Graduate School of Mathematics Nagoya University Nagoya Japan The Department of Computer Science and Technology Tsinghua University Beijing China The State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China

Lexicographically minimal string rotation (LMSR) is a problem to find the minimal one among all rotations of a string in the lexicographical order, which is widely used in equality checking of graphs, polygons, automata and chemical structures. In this paper, we propose an O(n3/4) quantum query algorithm for LMSR. In particular, the algorithm has average-case query complexity O(√n log n), which is shown to be asymptotically optimal up to a polylogarithmic factor, compared to its Ω (pn/ log n ) lower bound. Furthermore, we show that our quantum algorithm outperforms any (classical) randomized algorithms in both worst and average cases. As an application, it is used in benzenoid identification and disjoint-cycle automata minimization. Copyright © 2020, The Authors. All rights reserved.

关键词： Rotation

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Contour Detection from Ultrasound Kidney Images with A Coarse-to-Fine Approach

Contour Detection from Ultrasound Kidney Images with A Coars...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Tao Peng Yidong Gu Yanqing Xu Caishan Wang Lei Zhang Jing Cai School of Future Science and Engineering Soochow University Suzhou China Department of Radiation Oncology UT Southwestern Medical Center Dallas TX USA Department of Medical Ultrasound the Affiliated Suzhou Hospital of Nanjing Medical University Suzhou Municipal Hospital Suzhou Jiangsu China McDermott Center for Human Growth and Development University of Texas Southwestern Medical Center Dallas Texas USA Department of Ultrasound the Second Affiliated Hospital of Soochow University Suzhou China Graduate Program of Medical Physics and Data Science Research Center Duke Kunshan University Kunshan Jiangsu China Department of Health Technology and Informatics The Hong Kong Polytechnic University Hong Kong China

Ultrasound kidney image segmentation presents significant challenges due to missing or ambiguous boundaries. In this study, we introduce a coarse-to-refinement approach incorporating four novel aspects. Firstly, we leverage the properties of a principal curve (PC) to automatically fine-tune the curve shape and employ a neural network's learning ability to reduce model error. Secondly, a deep fusion learning network is utilized for the coarse segmentation step, incorporating a parallel architecture to enhance deep-learning performance. Thirdly, addressing the limitation of standard PC-based methods in determining the number of vertices automatically, we propose an automatic searching polygon tracking method using a mean shift clustering-based approach to replace the projection and vertex extension step in standard PC-based methods. Lastly, we develop an explainable mathematical map function for the kidney contour, as denoted by the neural network output (i.e., optimized vertices), which aligns well with the ground truth contour. We conducted various experiments to evaluate our method's performance, demonstrating its effectiveness in ultrasound kidney image segmentation.

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