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Author Correction: Random laser ablated tags for anticounterfeiting purposes and towards physically unclonable functions

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Nature communications 2024年第1期15卷 8772页

作者： Srinivas Gandla Jinsik Yoon Cheol-Woong Yang HyungJune Lee Wook Park Sunkook Kim Multifunctional Nano Bio Electronics Lab Department of Advanced Materials Science and Engineering Sungkyunkwan University Cheoncheon-dong Jangan-gu Suwon-si Gyeonggi-do 16419 Republic of Korea. Institute for Wearable Convergence Electronics Department of Electronics and Information Convergence Engineering Kyung Hee University Deogyeong-daero Giheung-gu Yongin-si Gyeonggi-do 17104 Republic of Korea. Electron Microscopy Research Laboratory Department of Advanced Materials Science and Engineering Sungkyunkwan University Cheoncheon-dong Jangan-gu Suwon-si Gyeonggi-do 16419 Republic of Korea. Intelligent Networked Systems Lab Department of Computer Science and Engineering Ewha Womans University Ewhayeodae-gil Seodaemun-gu Seoul 03760 Republic of Korea. Institute for Wearable Convergence Electronics Department of Electronics and Information Convergence Engineering Kyung Hee University Deogyeong-daero Giheung-gu Yongin-si Gyeonggi-do 17104 Republic of Korea. parkwook@khu.ac.kr. Multifunctional Nano Bio Electronics Lab Department of Advanced Materials Science and Engineering Sungkyunkwan University Cheoncheon-dong Jangan-gu Suwon-si Gyeonggi-do 16419 Republic of Korea. seonkuk@skku.edu.

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The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels (vol 400, pg 1619, 2022)

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LANCET 2022年第10365期400卷 1766-1766页

作者： Romanello, M. Di Napoli, C. Drummond, P. Institute for Global Health University College London London UK School of Agriculture Policy and Development University of Reading Reading UK Institute for Sustainable Resources University College London London UK Department of Global Health Centre for Health and the Global Environment University of Washington Seattle WA USA UCL Energy Institute University College London London UK Department of Health Sciences University of York York UK Department of Meteorology University of Reading Reading UK Institute for Risk and Disaster Reduction University College London London UK School of Earth and Environment University of Leeds Leeds UK Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London UK School of Population Health University of Melbourne Melbourne VIC Australia Department of Earth System Science Tsinghua University Beijing China Mercator Research Institute on Global Commons and Climate Change Berlin Germany Department of Environment Climate Change and Health World Health Organization Geneva Switzerland Institute of Environmental Sciences University of Geneva Geneva Switzerland Cardiovascular Epidemiology Unit Department of Public Health & Primary Care University of Cambridge Cambridge UK School of Government University of Birmingham Birmingham UK Economic Analysis of Climate Impacts and Policy Division Centro Euro-Mediterraneo sui Cambiamenti Climatici Venice Italy Institute for Environmental Design and Engineering University College London London UK Natural Resources Institute University of Greenwich London UK Department of Environmental Health Sciences and Yale Center on Climate Change and Health Yale University New Haven CT USA Department of Civil and Environmental Engineering Northeastern University Boston MA USA Department of Fish and Wildlife Conservation Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Geography University College London London UK NU

With advancements in the science of detection and attribution studies, the influence of climate change over many events has now been quantified. Because of the rapidly increasing temperatures, vulnerable populations (adults older than 65 years, and children younger than one year of age) were exposed to 3·7 billion more heatwave days in 2021 than annually in 1986–2005 (indicator 1.1.2), and heat-related deaths increased by 68% between 2000–04 and 2017–21 (indicator 1.1.5), a death toll that was significantly exacerbated by the confluence of the COVID-19 pandemic. Despite the local cooling and overall health benefits of urban greenspaces, only 277 (27%) of 1038 global urban centres were at least moderately green in 2021 (indicator 2.2.3), and the number of households with air conditioning increased by 66% from 2000 to 2020, a maladaptive response that worsens the energy crisis and further increases urban heat, air pollution, and greenhouse gas emissions. [...]millions of people do not have access to the energy needed to keep their homes at healthy temperatures, preserve food and medication, and meet the seventh Sustainable Development Goal (to ensure access to affordable, reliable, sustainable, and modern energy for all). Aggravating this situation even further, governments continue to incentivise fossil fuel production and consumption: 69 (80%) of 86 countries reviewed had net-negative carbon prices (ie, provided a net subsidy to fossil fuels) for a net total of US$400 billion

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A Benchmark System for Hardware-in-The-Loop Testing of Distributed Energy Resources

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IEEE Power and Energy Technology systems Journal 2018年第3期5卷 94-103页

作者： Kotsampopoulos, Panos Lagos, Dimitris Hatziargyriou, Nikos Faruque, M. Omar Lauss, Georg Nzimako, Onyi Forsyth, Paul Steurer, Michael Ponci, F. Monti, A. Dinavahi, V. Strunz, Kai Smart Grids Research Unit School of Electrical and Computer Engineering National Technical University of Athens Zografou15780 Greece Department of Electrical and Computer Engineering Center for Advanced Power Systems Florida State University TallahasseeFL32310 United States Energy Department Austrian Institute of Technology Vienna1210 Austria RTDS Inc. WinnipegMBR3T 2E1 Canada Institute for Automation of Complex Power Systems E.ON Energy Research Center RWTH Aachen University Aachen52074 Germany Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2V4 Canada SENSE Lab Berlin University of Technology Berlin10587 Germany

In order to overcome challenges associated with the integration of distributed energy resources (DER) into state-of-The-art and future power grids, a common basis for testing using appropriate benchmark systems is required. Real-time hardware-in-The-loop (HIL) simulation has proven to be an advanced and efficient tool for the analysis and validation of electric power systems and DER components. However, a common methodology for HIL testing of DER along with the required set of reference systems has not yet been developed. This task-force paper proposes a benchmark system for HIL testing incorporating DER into the real-time simulation environment. A low-voltage benchmark system with detailed HIL setup is proposed for the testing of DER performance. The modeling of DER for real-time applications is discussed, and the detailed laboratory procedures and setups for both controller HIL (CHIL) and power HIL (PHIL) are provided. Results from CHIL simulation related to the centralized controls and experimental results of PHIL simulation related to local control on the benchmark system substantiate the suitability of the proposed real-time simulation approach. © 2014 IEEE.

关键词： Hardware-in-the-loop simulation

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3D printed near-infrared high-numerical aperture achromatic metalens

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iScience 2025年第6期28卷

作者： Wei, Heming Hu, Wenchen Hu, Jingtian He, Guoqiang Pang, Fufei Krishnaswamy, Sridhar Nedoma, Jan Marques, Carlos Key Laboratory of Specialty Fiber Optics and Optical Access Networks Joint International Research Laboratory of Specialty Fiber Optics and Advanced Communication Shanghai University Shanghai 200444 China Ministry of Industry and Information Technology Key Lab of Micro-Nano Optoelectronic Information System Guangdong Provincial Key Laboratory of Semiconductor Optoelectronic Materials and Intelligent Photonic Systems Harbin Institute of Technology Shenzhen China Center for Smart Structures and Materials Department of Mechanical Engineering Northwestern University Evanston 60208 IL United States Department of Telecommunications VSB – Technical University of Ostrava Ostrava 70800 Czech Republic CICECO – Aveiro Institute of Materials Physics Department University of Aveiro Aveiro 3810-193 Portugal Department of Physics VSB—Technical University of Ostrava Ostrava 70800 Czech Republic

Traditional optical Fresnel microlenses have limitations such as large size, limited optical quality for imaging, and low focusing efficiency in achromatic lenses with high NA. In contrast, metalenses rely on their subwavelength structure to modulate the phase distribution, resulting in smaller volumes and superior focusing performance. In this work, we inverse designed and fabricated an achromatic metalens with high-NA and broad wavelength range through direct laser writing using the two-photon polymerization technique. With a focal length of 19 μm, a thickness of 3.6 μm, and a numerical aperture of 0.8, the metalens exhibits an average focusing efficiency of 53.6% and an average half maximum width of 1.27 μm at the working wavelength. The measured average focusing efficiency is 50.4% within the bandwidth range of 1510 nm–1610 nm. The presented work demonstrates the great potential of 3D printing and inverse design for realizing functional meta-devices for aerospace sector. © 2025 The Author(s)

关键词： Metamaterials Optical materials Optics Photonics

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Towards Reproducible Bioinformatics: The OpenBio-C Scientific Workflow Environment

Towards Reproducible Bioinformatics: The OpenBio-C Scientifi...

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IEEE Symposium on Bioinformatics and Bioengineering (BIBE)

作者： Alexandros Kanterakis Galateia Iatraki Konstantina Pityanou Lefteris Koumakis Nikos Kanakaris Nikos Karacapilidis George Potamias Foundation for Research and Technology-Hellas (FORTH) Institute of Computer Science Heraklion Greece Dept. of Electrical and Computer Engineering Hellenic Mediterranean University Heraklion Crete Greece Industrial Management and Information Systems Lab MEAD University of Patras Patras Greece

ISBN: (纸本)9781728146188

The highly competitive environment of post-genomics biomedical research is pushing towards the production of highly qualified results and their utilization in clinical practice. Due to this pressure, an important factor of scientific progress has been underestimated namely, the reproducibility of the results. To this end, it is critical to design and implement computational platforms that enable seamless and unhindered access to distributed bio-data, software and computational infrastructures. Furthermore, the need to support collaboration and form synergistic activities between the engaged researchers is also raised, as the mean to achieve consensus on respective scientific discoveries. The aforementioned needs and requirements underlie the motivations for the development of OpenBio-C workflow environment, and determine its fundamental objectives. The insufficiencies of current workflow editing and execution environments are explored, and the key-directions to advance over an environment that supports reproducibility are stated. The basic components and functionality of the OpenBio-C initial implementation (beta version) are detailed.

关键词： Bioinformatics Tools Collaboration Pipelines Genomics Market research Semantics

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Building an Aerial-Ground Robotics System for Precision Farming: An Adaptable Solution

arXiv

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arXiv 2019年

作者： Pretto, Alberto Aravecchia, Stéphanie Burgard, Wolfram Chebrolu, Nived Dornhege, Christian Falck, Tillmann Fleckenstein, Freya Fontenla, Alessandra Imperoli, Marco Khanna, Raghav Liebisch, Frank Lottes, Philipp Milioto, Andres Nardi, Daniele Nardi, Sandro Pfeifer, Johannes Popović, Marija Potena, Ciro Pradalier, Cédric Rothacker-Feder, Elisa Sa, Inkyu Schaefer, Alexander Siegwart, Roland Stachniss, Cyrill Walter, Achim Winterhalter, Wera Wu, Xiaolong Nieto, Juan Department of Computer Control and Management Engineering Sapienza University of Rome Rome Italy International Research Lab 2958 Georgia Tech-CNRS Metz France Department of Computer Science University of Freiburg Germany Toyota Research Institute Los Altos United States Photogrammetry & Robotics Lab University of Bonn Germany Robert Bosch GmbH Corporate Research Renningen Germany Osimo Italy Autonomous Systems Lab. Department of Mechanical and Process Engineering ETH Zurich Zürich Switzerland Department of Environmental Systems Science Institute of Agricultural Sciences ETH Zurich Zürich Switzerland IT+Robotics Srl Padova Italy Smart Robotics Lab. Department of Computing Imperial College London London United Kingdom CSIRO Data61 Australia

The application of autonomous robots in agriculture is gaining increasing popularity thanks to the high impact it may have on food security, sustainability, resource use efficiency, reduction of chemical treatments, and the optimization of human effort and yield. With this vision, the Flourish research project aimed to develop an adaptable robotic solution for precision farming that combines the aerial survey capabilities of small autonomous unmanned aerial vehicles (UAVs) with targeted intervention performed by multi-purpose unmanned ground vehicles (UGVs). This paper presents an overview of the scientific and technological advances and outcomes obtained in the project. We introduce multi-spectral perception algorithms and aerial and ground-based systems developed for monitoring crop density, weed pressure, crop nitrogen nutrition status, and to accurately classify and locate weeds. We then introduce the navigation and mapping systems tailored to our robots in the agricultural environment, as well as the modules for collaborative mapping. We finally present the ground intervention hardware, software solutions, and interfaces we implemented and tested in different field conditions and with different crops. We describe a real use case in which a UAV collaborates with a UGV to monitor the field and to perform selective spraying without human intervention. Copyright © 2019, The Authors. All rights reserved.

关键词： Mapping

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THz near-field imaging of extreme subwavelength metal structures

arXiv

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arXiv 2021年

作者： Chen, Xinzhong Liu, Xiao Guo, Xiangdong Chen, Shu Hu, Hai Nikulina, Elizaveta Yao, Ziheng Betchel, Hans Martin, Michael C. Carr, G. Lawrence Dai, Qing Zhuang, Songlin Hu, Qing Zhu, Yiming Hillenbrand, Rainer Liu, Mengkun You, Guanjun Department of Physics and Astronomy Stony Brook University Stony BrookNY11794 United States Shanghai Key Lab of Modern Optical Systems Terahertz Technology Innovation Research Institute Engineering Research Center of Optical Instrument and System Ministry of Education University of Shanghai for Science and Technology Shanghai200093 China Division of Nanophotonics CAS Center for Excellence in Nanoscience National Center for Nanoscience and Technology Beijing100190 China CIC nanoGUNE Donostia-San Sebastián20018 Spain CIC nanoGUNE UPV/EHU Donostia-San Sebastián20018 Spain IKERBARSQUE Basque Foundation of Science Bilbao48013 Spain Advanced Light Source Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States National Synchrotron Light Source II Brookhaven National Laboratory UptonNY11973 United States Department of Electrical Engineering and Computer Science Research Laboratory of Electronics Massachusetts Institute of Technology CambridgeMA02139 United States

Modern scattering-type scanning near-field optical microscopy (s-SNOM) has become an indispensable tool in material research. However, as the s-SNOM technique marches into the far-infrared (IR) and terahertz (THz) regimes, emerging experiments sometimes produce puzzling results. For example, "anomalies" in the near-field optical contrast have been widely reported. In this letter, we systematically investigate a series of extreme subwavelength metallic nanostructures via s-SNOM near-field imaging in the GHz to THz frequency range. We find that the near-field material contrast is greatly impacted by the lateral size of the nanostructure, while the spatial resolution is practically independent of it. The contrast is also strongly affected by the connectivity of the metallic structures to a larger metallic "ground plane". The observed effect can be largely explained by a quasi-electrostatic analysis. We also compare the THz s-SNOM results to those of the mid-IR regime, where the size-dependence becomes significant only for smaller structures. Our results reveal that the quantitative analysis of the near-field optical material contrasts in the long-wavelength regime requires a careful assessment of the size and configuration of metallic (optically conductive) structures. Copyright © 2021, The Authors. All rights reserved.

关键词： Metals

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Corrigendum to “Blockchain-empowered sustainable manufacturing and product lifecycle management in industry 4.0: A survey” [Renew Sustain Energy Rev 132 (2020) 110112]

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Renewable and Sustainable Energy Reviews 2022年 167卷

作者： Jiewu Leng Guolei Ruan Pingyu Jiang Kailin Xu Qiang Liu Xueliang Zhou Chao Liu Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangdong University of Technology Guangzhou 510006 China Shenzhen Research Institute City University of Hong Kong Shenzhen 518057 China State Key Lab for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an 710064 China School of Mechanical Engineering Hubei University of Automotive Technology Shiyan 442002 China School of Mechatronics & Vehicle Engineering Chongqing Jiaotong University Chongqing 400074 China

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Why is the Winner the Best?

Why is the Winner the Best?

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Conference on computer Vision and Pattern Recognition (CVPR)

作者： M. Eisenmann A. Reinke V. Weru M. D. Tizabi F. Isensee T. J. Adler S. Ali V. Andrearczyk M. Aubreville U. Baid S. Bakas N. Balu S. Bano J. Bernal S. Bodenstedt A. Casella V. Cheplygina M. Daum M. De Bruijne A. Depeursinge R. Dorent J. Egger D. G. Ellis S. Engelhardt M. Ganz N. Ghatwary G. Girard P. Godau A. Gupta L. Hansen K. Harada M. Heinrich N. Heller A. Hering A. Huaulmé P. Jannin A. E. Kavur O. Kodym M. Kozubek J. Li H. Li J. Ma C. Martín-Isla B. Menze A. Noble V. Oreiller N. Padoy S. Pati K. Payette T. Rädsch J. Rafael-Patiño V. Singh Bawa S. Speidel C. H. Sudre K. Van Wijnen M. Wagner D. Wei A. Yamlahi M. H. Yap C. Yuan M. Zenk A. Zia D. Zimmerer D. Aydogan B. Bhattarai L. Bloch R. Brüngel J. Cho C. Choi Q. Dou I. Ezhov C. M. Friedrich C. Fuller R. R. Gaire A. Galdran Á. García Faura M. Grammatikopoulou S. Hong M. Jahanifar I. Jang A. Kadkhodamohammadi I. Kang F. Kofler S. Kondo H. Kuijf M. Li M. Luu T. Martinčič P. Morais M. A. Naser B. Oliveira D. Owen S. Pang J. Park S. Park S. Płotka E. Puybareau N. Rajpoot K. Ryu N. Saeed A. Shephard P. Shi D. Štepec R. Subedi G. Tochon H. R. Torres H. Urien J. L. Vilaça K. A. Wahid H. Wang J. Wang L. Wang X. Wang B. Wiestler M. Wodzinski F. Xia J. Xie Z. Xiong S. Yang Y. Yang Z. Zhao K. Maier-Hein P. F. Jäger A. Kopp-Schneider L. Maier-Hein Division of Intelligent Medical Systems German Cancer Research Center (DKFZ) Heidelberg Germany Helmholtz Imaging German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Mathematics and Computer Science Heidelberg University Heidelberg Germany Division of Biostatistics German Cancer Research Center (DKFZ) Heidelberg Germany Division of Medical Image Computing German Cancer Research Center (DKFZ) Heidelberg Germany Faculty of Engineering and Physical Sciences School of Computing University of Leeds Leeds UK Institute of Informatics School of Management HES-SO Valais-Wallis University of Applied Sciences and Arts Western Switzerland Sierre Switzerland Department of Nuclear Medicine and Molecular Imaging Lausanne University Hospital Lausanne Switzerland Technische Hochschule Ingolstadt Ingolstadt Germany Center for Artificial Intelligence and Data Science for Integrated Diagnostics (AI2D) and Center for Biomedical Image Computing and Analytics (CBICA) University of Pennsylvania Philadelphia PA USA Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology Perelman School of Medicine University of Pennsylvania Philadelphia PA USA Department of Radiology University of Washington Seattle WA USA Department of Computer Science Wellcome/EPSRC Centre for Interventional and Surgical Sciences (WEISS) University College London London UK Universitat Autònoma de Barcelona & Computer Vision Center Barcelona Spain Division of Translational Surgical Oncology National Center for Tumor Diseases (NCT/UCC) Dresden Dresden Germany Department of Advanced Robotics Istituto Italiano di Tecnologia Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy IT University of Copenhagen Copenhagen Denmark Department of General Visceral and Transplantation Surgery Heidelberg University Hospital Heidelberg Germany Department of Radiology and Nuc

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.

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Transmission and Latency-Aware Load Balancing for Fog Radio Access Networks

Transmission and Latency-Aware Load Balancing for Fog Radio ...

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2018 IEEE Global Communications Conference, GLOBECOM 2018

作者： Mukherjee, Mithun Liu, Yejun Lloret, Jaime Guo, Lei Matam, Rakesh Aazam, Mohammad Guangdong Provincial Key Lab of Petrochemical Equipment Fault Diagnosis Guangdong University of Petrochemical Technology Maoming China Smart Systems Lab School of Computer Science and Engineering Northeastern University Shenyang China Universidad Politecnica de Valencia Valencia Spain Department of Computer Science and Engineering Indian Institute of Information Technology Guwahati India Carnegie Mellon University United States

ISBN: (纸本)9781538647288;9781538647271

Fog computing-based radio access networks (F-RANs) aim to extend the computing and storage facilities of the centralized cloud radio access networks (C-RANs) to the network edge. Compared with the centralized baseband unit pool in the C-RAN, F-RAN reduces the burden on fronthaul. Thus, the F-RAN is foreseen as a viable solution towards ultra-low latency service provisioning. However, due to limited computing and storage facilities in fog computing-enabled access points (F-APs), some tasks that cannot be executed on the primary F-APs are transferred to other F-APs. In worst-case, the tasks are sent to the resource-enriched centralized cloud for processing. The transmission latency between F-APs, F-AP-to-end- user, and fronthaul latency strongly depends on interference power from the undesired network element as well as end-users. At the same time, the computational latency increases with the queuing delay. In this paper, we propose a load balancing scheme to address the tradeoff between transmission and computing latencies in F- RANs. Finally, the extensive simulation results show that the proposed scheme outperforms the greedy approach to meet the critical requirements, such as low-latency and minimal task offloading to the cloud in the F-RAN for the low-latency communications. © 2018 IEEE.

关键词： Fog computing

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