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arXiv 2024年

作者： Yang, Ziduo Zhao, Yi-Ming Wang, Xian Liu, Xiaoqing Zhang, Xiuying Li, Yifan Lv, Qiujie Chen, Calvin Yu-Chian Shen, Lei Department of Mechanical Engineering National University of Singapore Singapore117575 Singapore Artificial Intelligence Medical Research Center School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Shenzhen518107 China Department of Physics National University of Singapore Singapore117551 Singapore -Preferred Program School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China State Key Laboratory of Chemical Oncogenomics School of Chemical Biology and Biotechnology Peking University Shenzhen Graduate School Shenzhen518055 China Department of Medical Research China Medical University Hospital Taichung40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung41354 Taiwan Guangdong L-Med Biotechnology Co. Ltd. Guangdong Meizhou514699 China Research Institute Chongqing401123 China

In computational molecular and materials science, determining equilibrium structures is the crucial first step for accurate subsequent property calculations. However, the recent discovery of millions of new crystals and complex twisted structures has challenged traditional computational methods, both ab initio and machine-learning-based, due to their computationally intensive iterative processes. To address these scalability issues, here we introduce DeepRelax, a deep generative model capable of performing geometric crystal structure relaxation rapidly and without iterations. DeepRelax learns the equilibrium structural distribution, enabling it to predict relaxed structures directly from their unrelaxed ones. The ability to perform structural relaxation at the millisecond level per structure, combined with the scalability of parallel processing, makes DeepRelax particularly useful for large-scale virtual screening. We demonstrate DeepRelax's reliability and robustness by applying it to five diverse databases, including oxides, Materials Project, two-dimensional materials, van der Waals crystals, and crystals with point defects. DeepRelax consistently shows high accuracy and efficiency, validated by density functional theory calculations. Finally, we enhance its trustworthiness by integrating uncertainty quantification. This work significantly accelerates computational workflows, offering a robust and trustworthy machine-learning method for material discovery and advancing the application of AI for science. Code for DeepRelax is available at https://***/Shen-Group/DeepRelax. Copyright © 2024, The Authors. All rights reserved.

关键词： Point defects

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Photonic Terahertz Phased Array

arXiv

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arXiv 2024年

作者： Niu, Li Feng, Xi Zhang, Xueqian Lu, Yongchang Wang, Qingwei Xu, Quan Chen, Xieyu Ma, Jiajun Qiu, Haidi Sha, Wei E.I. Zhang, Shuang Alù, Andrea Zhang, Weili Han, Jiaguang Center for Terahertz Waves College of Precision Instrument and Optoelectronics Engineering The Key Laboratory of Optoelectronics Information and Technology Tianjin University Tianjin300072 China Key Laboratory of Micro-nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science & Electronic Engineering Zhejiang University Hangzhou310027 China Department of Electrical & Electronic Engineering University of Hong Kong 999077 Hong Kong Photonics Initiative Advanced Science Research Center City University of New York New York10031 United States Physics Program Graduate Center City University of New York New York10016 United States School of Electrical and Computer Engineering Oklahoma State University StillwaterOK74078 United States Guangxi Key Laboratory of Optoelectronic Information Processing School of Optoelectronic Engineering Guilin University of Electronic Technology Guilin541004 China

Phased arrays are crucial in various technologies, such as radar and wireless communications, due to their ability to precisely control and steer electromagnetic waves. This precise control improves signal processing and enhances imaging performance. However, extending phased arrays to the terahertz (THz) frequency range has proven challenging, especially for high-frequency operation, broadband performance, two-dimensional (2D) phase control with large antenna arrays, and strong phase modulation. Here, we introduce a photonic platform to realize a THz phased array that bypasses the above challenges. Our method employs 2D phase coding with 2-bit across a broad THz frequency range from 0.8 to 1.4 THz. The core of our design is a pixelated nonlinear Pancharatnam-Berry metasurface driven by a spatially modulated femtosecond laser, allowing precise phase control of THz signals. We showcase the effectiveness of our method through four proof-of-concept applications: single beamforming, dual beamforming, imaging and vortex beam generation. The realized photonic platform provides a promising pathway for developing broadband phased arrays in the THz regime. Copyright © 2024, The Authors. All rights reserved.

关键词： Terahertz waves

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The Use of Social News Curation to Empower Citizens and Journalists: Findings of A Focus Group Study with Professional Curators

The Use of Social News Curation to Empower Citizens and Jour...

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International Conference on computer Supported Cooperative Work in Design

作者： Daniel Schneider António Correia Jano Moreira de Souza Tercio Pacitti Institute of Computer Applications and Research NCE/UFRJ Rio de Janeiro Brazil INESC TEC and University of Tràs-os-Montes e Alto Douro Vila Real Portugal Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil

ISBN: (纸本)9781728165981

Citizen engagement in building user-curated narratives of complex or long-lasting news stories has been the key foundation of the design and implementation of the Acropolis virtual environment. Previous user studies have shown, by positive evidence, that this goal can be pragmatically achieved, but the challenge now lies in assessing: a) the extent to which an environment like Acropolis can be used to empower citizens; and b) whether and how the tool could be used to support the work of professional curators. Findings from a focus group study highlighted the tool's potential to engage citizens with news, the usefulness of the environment to build virtual memories, and the convenience of using Acropolis to support professional journalistic work.

关键词： Conferences Buildings Virtual environments Tools Collaborative work

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MaxHiC: A robust background correction model to identify biologically relevant chromatin interactions in Hi-C and capture Hi-C experiments (vol 18, e1010241, 2022)

引用

PLOS COMPUTATIONAL BIOLOGY 2022年第9期18卷 e1010241页

作者： Alinejad-Rokny, Hamid Modegh, Rassa Ghavami Rabiee, Hamid R. Sarbandi, Ehsan Ramezani Rezaie, Narges Tam, Kin Tung Forrest, Alistair R. R. Harry Perkins Institute of Medical Research QEII Medical Centre and Centre for Medical Research The University of Western Australia Perth Australia Bio Medical Machine Learning Lab (BML) The Graduate School of Biomedical Engineering UNSW Sydney Sydney Australia Health Data Analytics Program AI-enabled Processes (AIP) Research Centre Macquarie University Sydney Australia Bioinformatics and Computational Biology Lab Department of Computer Engineering Sharif University of Technology Tehran Iran Center for Complex Biological Systems University of California Irvine Irvine California United States of America

Hi-C is a genome-wide chromosome conformation capture technology that detects interactions between pairs of genomic regions and exploits higher order chromatin structures. Conceptually Hi-C data counts interaction frequencies between every position in the genome and every other position. Biologically functional interactions are expected to occur more frequently than transient background and artefactual interactions. To identify biologically relevant interactions, several background models that take biases such as distance, GC content and mappability into account have been proposed. Here we introduce MaxHiC, a background correction tool that deals with these complex biases and robustly identifies statistically significant interactions in both Hi-C and capture Hi-C experiments. MaxHiC uses a negative binomial distribution model and a maximum likelihood technique to correct biases in both Hi-C and capture Hi-C libraries. We systematically benchmark MaxHiC against major Hi-C background correction tools including Hi-C significant interaction callers (SIC) and Hi-C loop callers using published Hi-C, capture Hi-C, and Micro-C datasets. Our results demonstrate that 1) Interacting regions identified by MaxHiC have significantly greater levels of overlap with known regulatory features (e.g. active chromatin histone marks, CTCF binding sites, DNase sensitivity) and also disease-associated genome-wide association SNPs than those identified by currently existing models, 2) the pairs of interacting regions are more likely to be linked by eQTL pairs and 3) more likely to link known regulatory features including known functional enhancer-promoter pairs validated by CRISPRi than any of the existing methods. We also demonstrate that interactions between different genomic region types have distinct distance distributions only revealed by MaxHiC. MaxHiC is publicly available as a python package for the analysis of Hi-C, capture Hi-C and Micro-C data.

关键词： Genomics Chromatin Genome-wide association studies Single nucleotide polymorphisms Histones Gene regulation Deoxyribonucleases Insulators

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Terahertz Magnetospectroscopy of Gadolinium Gallium Garnet in Fields up to 25 T

Terahertz Magnetospectroscopy of Gadolinium Gallium Garnet i...

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JSAP-OSA Joint Symposia, JSAP 2021

作者： Bao, J. Peraca, N. Marquez Tay, F. Kritzell, T.E. Li, X. Noe, G.T. Katayama, I. Takeda, J. Nojiri, H. Yamahara, H. Tabata, H. Baydin, A. Kono, J. Department of Physics and Astronomy Rice University HoustonTX United States Department of Electrical and Computer Engineering Rice University HoustonTX United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX United States Department of Physics Graduate School of Engineering Science Yokohama National University Yokohama Japan Institute for Materials Research Tohoku University Sendai Japan Department of Electrical Engineering and Information Systems Graduate School of Engineering University of Tokyo Japan Smalley-Curl Institute Rice University HoustonTX United States Department of Materials Science and NanoEngineering Rice University HoustonTX United States

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A Normal Distribution Transform-Based Radar Odometry Designed For Scanning and Automotive Radars

arXiv

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arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh Graduate Degree Program of Robotics National Chiao Tung University Hsinchu Taiwan Department of Electrical and Computer Engineering National Chiao Tung University The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan Department of Computer Science National Chiao Tung University Hsinchu Taiwan

Existing radar sensors can be classified into automotive and scanning radars. While most radar odometry (RO) methods are only designed for a specific type of radar, our RO method adapts to both scanning and automotive radars. Our RO is simple yet effective, where the pipeline consists of thresholding, probabilistic submap building, and an NDT-based radar scan matching. The proposed RO has been tested on two public radar datasets: the Oxford Radar RobotCar dataset and the nuScenes dataset, which provide scanning and automotive radar data respectively. The results show that our approach surpasses state-of-the-art RO using either automotive or scanning radar by reducing translational error by 51% and 30%, respectively, and rotational error by 17% and 29%, respectively. Besides, we show that our RO achieves centimeter-level accuracy as lidar odometry, and automotive and scanning RO have similar accuracy. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

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COVID-19 as Opportunity to Test Digital Nomad Lifestyle

COVID-19 as Opportunity to Test Digital Nomad Lifestyle

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International Conference on computer Supported Cooperative Work in Design

作者： Marcos Antonio de Almeida António Correia Daniel Schneider Jano Moreira de Souza Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil INESC TEC and University of Trás-os-Montes e Alto Douro Vila Real Portugal Tércio Pacitti Institute of Computer Applications and Research NCE/UFRJ Rio de Janeiro Brazil

ISBN: (纸本)9781728165974;9781728165981

We report the first findings of an empirical study aimed at investigating how COVID-19 pandemic has impacted the work practices and lifestyles of digital nomads (DN). To do this, we analyzed messages, questions and comments posted by digital nomads in a specific online discussion community of the Reddit social network. Preliminary findings indicate COVID-19 as an opportunity to test DN lifestyle by aspiring digital nomads who want to plan their careers and also present evidence of an overload of online channels for actual DNs. On the other hand, we found that much of the literature on digital nomadism is fragmented and scattered through different disciplines and perspectives, with a strong focus on digital nomads' lifestyles. In order to obtain a holistic and unified understanding of digital nomads, we conducted a comprehensive literature review to further conceptualize the phenomenon under study.

关键词： COVID-19 Social networking (online) Pandemics engineering profession Conferences Bibliographies Collaborative work

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Accelerating adoption of species-agnostic plant sensors for precision farming

Nature Reviews Electrical Engineering

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Nature Reviews Electrical engineering 2025年 58-70页

作者： Abdullah Bukhamsin Khaled Nabil Salama Jürgen Kosel Ikram Blilou Bioengineering Program Biological and Environmental Science and Engineering (BESE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Center of Excellence — Sustainable Food Security (SFS) King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Electrical and Computer Engineering Program Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia Sensor Systems Division Silicon Austria Labs Villach Austria Plant Science Program Biological and Environmental Science and Engineering (BESE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

Precision farming is an optimized management farming scheme that seeks to link the real-time needs of crops with the nutrients to be administered. Sensing platforms that can monitor the physiological status of crops in situ are key to enabling timely and localized interventions. However, the underdevelopment of plant sensing strategies limits the potential of precision farming. In this Review, we discuss the challenges and advancements in phyto-monitoring, focusing on strategies that are applicable to a wide range of plant species and suitable for field deployment. We explore species-agnostic sensors, including optical and electrochemical sensors, whose operation is based on principles that are widely applicable to all plant species. These platforms enable real-time monitoring of the physiological state of crops by assessing key biomarkers, such as plant hormones, and metabolites such as salicylic acid and reactive oxygen species. Evaluating these systems, we conclude that an integrative sensing approach is necessary to compensate for the limitations of the individual methods and can provide a holistic view of crop health. Cost-effective species-agnostic sensors are thus needed to provide information that can be used to minimize the resource footprint of farming and meet the growing global demand.

关键词：

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Crowdsourcing Urban Narratives for a Post-Pandemic World

Crowdsourcing Urban Narratives for a Post-Pandemic World

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International Conference on computer Supported Cooperative Work in Design

作者： Ramon Chaves Daniel Schneider Claudia Motta António Correia Hugo Paredes Bárbara Caetano Jano Moreira de Souza Postgraduate Program in Informatics PPGI/UFRJ Rio de Janeiro Brazil Tércio Pacitti Institute of Computer Applications and Research (NCE) Federal University of Rio de Janeiro Brazil INESC TEC and University of Trás-os-Montes e Alto Douro UTAD Vila Real Portugal Systems Engineering and Computer Science Program (PESC/COPPE/UFRJ) Rio de Janeiro Brazil

ISBN: (纸本)9781728165974;9781728165981

Over the past decades, the use of digital technologies to support participatory urban planning and design has been repeatedly described as a crucial instrument and critical building block for tackling historical problems of participation in such processes. Social media, e-participation platforms, and crowdsourcing applications are examples of technologies that can involve citizens in decision-making processes and thus leverage the benefits of collective intelligence. However, despite the extensive use of social media platforms, old problems related to engagement and participation still occur in digital initiatives. Successful collaboration examples between citizens, policymakers, and strategic stakeholders are still scarce based on online social practices. This study aims to introduce a collective intelligence model, which combines crowdsourcing and social storytelling to support participatory urban planning and design from a bottom-up perspective. The paper concludes by discussing a scenario where citizens can engage in mapping, taking photos, sending ideas, or even creating collective stories about their university issues in a post-pandemic future.

关键词： Crowdsourcing Social networking (online) Smart cities Instruments Urban planning Collective intelligence Tools

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Simplified belief-dependent reward mcts planning with guaranteed tree consistency

arXiv

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arXiv 2021年

作者： Sztyglic, Ori Zhitnikov, Andrey Indelman, Vadim Department of Computer Science Technion - Israel Institute of Technology Haifa32000 Israel Technion Autonomous Systems Program Technion - Israel Institute of Technology Haifa32000 Israel Department of Aerospace Engineering Technion - Israel Institute of Technology Haifa32000 Israel

Partially Observable Markov Decision Processes (POMDPs) are notoriously hard to solve. Most advanced state-of-the-art online solvers leverage ideas of Monte Carlo Tree Search (MCTS). These solvers rapidly converge to the most promising branches of the belief tree, avoiding the suboptimal sections. Most of these algorithms are designed to utilize straightforward access to the state reward and assume the belief-dependent reward is nothing but expectation over the state reward. Thus, they are inapplicable to a more general and essential setting of belief-dependent rewards. One example of such reward is differential entropy approximated using a set of weighted particles of the belief. Such an information-theoretic reward introduces a significant computational burden. In this paper, we embed the paradigm of simplification into the MCTS algorithm. In particular, we present Simplified Information-Theoretic Particle Filter Tree (SITH-PFT), a novel variant to the MCTS algorithm that considers information-theoretic rewards but avoids the need to calculate them completely. We replace the costly calculation of information-theoretic rewards with adaptive upper and lower bounds. These bounds are easy to calculate and tightened only by the demand of our algorithm. Crucially, we guarantee precisely the same belief tree and solution that would be obtained by MCTS, which explicitly calculates the original information-theoretic rewards. Our approach is general;namely, any converging to the reward bounds can be easily plugged-in to achieve substantial speedup without any loss in performance. © 2021, CC BY.

关键词： Information theory

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