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arXiv 2024年

作者： Fang, Jie Chen, Rui Sharp, David Renzi, Enrico M. Manna, Arnab Kala, Abhinav Mann, Sander A. Yao, Kan Munley, Christopher Rarick, Hannah Tang, Andrew Pumulo, Sinabu Zheng, Yuebing Menon, Vinod M. Alù, Andrea Majumdar, Arka Department of Electrical and Computer Engineering University of Washington SeattleWA98195 United States Department of Physics University of Washington SeattleWA98195 United States Photonics Initiative Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York New YorkNY10016 United States Walker Department of Mechanical Engineering Texas Materials Institute The University of Texas at Austin AustinTX78712 United States Department of Materials Science and Engineering University of Washington SeattleWA98195 United States Department of Physics City College of New York New YorkNY10031 United States

High-quality (Q)-factor optical resonators with extreme temporal coherence are of both technological and fundamental importance in optical metrology1,2, continuous-wave lasing3-5, and semiconductor quantum optics6-8. Despite extensive efforts in designing high-Q resonators across different spectral regimes, the experimental realization of very large Q-factors at visible wavelengths remains challenging due to the small feature size that is sensitive to fabrication imperfections9-12, and thus is typically implemented in integrated photonics1-4,9,10. In the pursuit of free-space optics with the benefits of large space-bandwidth product and massive parallel operations13,14, here we design and fabricate a visible-wavelength etch-free metasurface with minimized fabrication defects and experimentally demonstrate a million-scale ultrahigh-Q resonance. A new laser-scanning momentum-space-resolved spectroscopy technique with extremely high spectral and angular resolution is developed to characterize the record-high Qfactor as well as the dispersion of the million-Q resonance in free space. By integrating monolayer WSe2 into our ultrahigh-Q meta-resonator, we further demonstrate laser-like highly unidirectional and narrow-linewidth exciton emission, albeit without any operating power density threshold. Under continuous-wave laser pumping, we observe pump-power-dependent linewidth narrowing at room temperature, indicating the potential of our meta-optics platform in controlling coherent quantum light-sources. Our result also holds great promise for applications like optical sensing, spectral filtering, and few-photon nonlinear optics. Copyright © 2024, The Authors. All rights reserved.

关键词： Continuous wave lasers

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TargetNet: Functional microRNA target prediction with deep neural networks

arXiv

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arXiv 2021年

作者： Min, Seonwoo Lee, Byunghan Yoon, Sungroh Department of Electrical and Computer Engineering Seoul National University Seoul08826 Korea Republic of LG AI Research Seoul07796 Korea Republic of Department of Electronic and IT Media Engineering Seoul National University of Science and Technology Seoul01811 Korea Republic of Interdisciplinary Program in Artificial Intelligence and Interdisciplinary Program in Bioinformatics Seoul National University Seoul08826 Korea Republic of

Motivation: MicroRNAs (miRNAs) play pivotal roles in gene expression regulation by binding to target sites of messenger RNAs (mRNAs). While identifying functional targets of miRNAs is of utmost importance, their prediction remains a great challenge. Previous computational algorithms have major limitations. They use conservative candidate target site (CTS) selection criteria mainly focusing on canonical site types, rely on laborious and time-consuming manual feature extraction, and do not fully capitalize on the information underlying miRNA-CTS interactions. Results: In this paper, we introduce TargetNet, a novel deep learning-based algorithm for functional miRNA target prediction. To address the limitations of previous approaches, TargetNet has three key components: (1) relaxed CTS selection criteria accommodating irregularities in the seed region, (2) a novel miRNA-CTS sequence encoding scheme incorporating extended seed region alignments, and (3) a deep residual network-based prediction model. The proposed model was trained with miRNA-CTS pair datasets and evaluated with miRNA-mRNA pair datasets. TargetNet advances the previous state-of-theart algorithms used in functional miRNA target classification. Furthermore, it demonstrates great potential for distinguishing high-functional miRNA targets. © 2021, CC BY-NC-ND.

关键词： RNA

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Electron mobility of SnO2 from first principles

arXiv

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arXiv 2024年

作者： Wang, Amanda Bushick, Kyle Pant, Nick Lee, Woncheol Zhang, Xiao Leveillee, Joshua Giustino, Feliciano Poncé, Samuel Kioupakis, Emmanouil Department of Materials Science and Engineering University of Michigan Ann ArborMI48109 United States Applied Physics Program University of Michigan Ann ArborMI48109 United States Department of Electrical and Computer Engineering University of Michigan Ann ArborMI48109 United States Oden Institute for Computational Engineering and Sciences The University of Texas at Austin AustinTX78712 United States Department of Physics The University of Texas at Austin AustinTX78712 United States European Theoretical Spectroscopy Facility Institute of Condensed Matter and Nanosciences Université catholique de Louvain Chemin des Étoiles 8 Louvain-la-NeuveB-1348 Belgium WEL Research Institute Avenue Pasteur 6 Wavre1300 Belgium

The transparent conducting oxide SnO2 is a wide bandgap semiconductor that is easily n-type doped and widely used in various electronic and optoelectronic applications. Experimental reports of the electron mobility of this material vary widely depending on the growth conditions and doping concentrations. In this work, we calculate the electron mobility of SnO2 from first principles to examine the temperature- and doping-concentration dependence, and to elucidate the scattering mechanisms that limit transport. We include both electron-phonon scattering and electron-ionized impurity scattering to accurately model scattering in a doped semiconductor. We find a strongly anisotropic mobility that favors transport in the direction parallel to the c-axis. At room temperature and intrinsic carrier concentrations, the low-energy polar-optical phonon modes dominate scattering, while ionized-impurity scattering dominates above 1018 cm-3 Copyright © 2024, The Authors. All rights reserved.

关键词： Electron mobility

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Internet of Things in disaster management systems: A systematic review

引用

AIP Conference Proceedings 2023年第1期2594卷

作者： G. P. L. Barnabas H. Citrawati T. A. Santoso N. Surantha Computer Science Department BINUS Graduate Program-Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Department of Electrical Electronic and Communication Engineering Faculty of Engineering Tokyo City University Tamazutsumi 1-28-1 Setagaya City Tokyo 158-8557 Japan

Disasters are unexpected, sudden events that may cause monumental damages to both materials and human lives. Hence, the unpredictability and destruction that follow when a disaster happens to pose a dire challenge for researchers, scientists, and governments to find ways to effectively handle the situation and flow of information when such an event strikes. The Internet of Things (IoT) presents a solution that involves using one or more mobile devices connected over the network, thus making the transfer of data and information more effective and efficient. This paper presents a holistic analysis of the state-of-the-art IoT technologies which can answer the challenge posed above, in addition to the demand for efficiency, mobility, accuracy, as well as better communications between the command center and all actors involved in disaster operations. The applications of IoT have varied for many purposes. We divide those purposes into two broad strokes of pre-disaster management and post-disaster management IoT-aided systems. For pre-disaster management, the IoT-aided systems are mostly used to predict the possible disaster that might happen using sensors placed in strategic places. Finally, for post-disaster management, the IoT-aided systems aid in improving the effectiveness and accuracy of evacuation, relief, and victim-tracking efforts.

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An infrastructure for creating web automation applications 16

An infrastructure for creating web automation applications

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16th Conference on Computational Linguistics and Speech Processing, ROCLING 2004

作者： Yen, Wen Heng Ke, Hao-Ren Yang, Wei-Pang Degree Program of Electrical Engineering and Computer Science National Chiao Tung University 1001 Ta Hsueh Rd. Hsinchu30050 Taiwan University Library National Chiao Tung University 1001 Ta Hsueh Rd. Hsinchu30050 Taiwan Dept. of Computer and Information Science National Chiao Tung University 1001 Ta Hsueh Rd. Hsinchu30050 Taiwan Dept. of Information Management National Dong Hwa University 1 Sec. 2 Da Hsueh Rd. Shou-Feng Hualien97401 Taiwan

With the growth of the World Wide Web (WWW), many people nowadays spend a lot of time performing various tasks with browsers, most of these tasks repetitive and tedious. Many applications are created to reorganize and simplify the usage of Web resources, which are called Web automation applications. This paper proposes an infrastructure to create Web automation applications, the WIS (Web Integration Solution) system. WIS integrates a diversity of tools and technologies to provide a software environment for developing Web automation services. Developers can use this tool to create various Web automation applications. We show the versatility of WIS by implementing three exemplary services. The first is a metasearcher system that provides a single search interface for several indexing and abstract databases. The second is a cataloguing tool to simplify the task of retrieving bibliographic data from the Web;this tool is also integrated with a book-recommendation system for libraries. The third is a Web site checking system that periodically checks if some critical Web sites are working correctly, no matter how complex the check procedure is. © Proc. of the 16th Conference on Computational Linguistics and Speech Processing, ROCLING 2004. All rights reserved.

关键词： Websites

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No winners: Performance of lung cancer prediction models depends on screening-detected, incidental, and biopsied pulmonary nodule use cases.

arXiv

引用

arXiv 2024年

作者： Li, Thomas Z. Xu, Kaiwen Krishnan, Aravind Gao, Riqiang Kammer, Michael N. Antic, Sanja Xiao, David Knight, Michael Martinez, Yency Paez, Rafael Lentz, Robert J. Deppen, Stephen Grogan, Eric L. Lasko, Thomas A. Sandler, Kim L. Maldonado, Fabien Landman, Bennett A. Medical Scientist Training Program Vanderbilt University NashvilleTN37235 United States Biomedical Engineering Vanderbilt University NashvilleTN37235 United States Computer Science Vanderbilt University NashvilleTN37235 United States Electrical and Computer Engineering Vanderbilt University NashvilleTN37235 United States Digital Technology and Innovation Siemens Healthineers PrincetonNJ08540 United States Division of Allergy Pulmonary and Critical Care Medicine Department of Medicine Vanderbilt University Medical Center NashvilleTN37232 United States Department of Thoracic Surgery Vanderbilt University Medical Center NashvilleTN37232 United States Biomedical Informatics Vanderbilt University Medical Center NashvilleTN37232 United States Radiology and Radiological Sciences Vanderbilt University Medical Center NashvilleTN37232 United States

Purpose: Statistical models for predicting lung cancer have the potential to facilitate earlier diagnosis of malignancy and avoid invasive workup of benign disease. Many models have been published, but comparative studies of their utility in different clinical settings in which patients would arguably most benefit are scarce. Materials and Methods: This study retrospectively evaluated promising predictive models for lung cancer prediction in three clinical settings: lung cancer screening with low-dose computed tomography, incidentally detected pulmonary nodules, and nodules deemed suspicious enough to warrant a biopsy. We leveraged 9 cohorts (n=898, 896, 882, 219, 364, 117, 131, 115, 373) from multiple institutions to assess the area under the receiver operating characteristic curve (AUC) of validated models including logistic regressions on clinical variables and radiologist nodule characterizations, artificial intelligence on chest CTs, longitudinal imaging AI, and multi-modal approaches. We implemented each model from their published literature, re-training the models if necessary, and curated each cohort from primary data sources. Results: We observed that model performance varied greatly across clinical use cases. No single predictive model emerged as a clear winner across all cohorts, but certain models excelled in specific clinical contexts. Single timepoint chest CT AI performed well in lung screening, but struggled to generalize to other clinical settings. Longitudinal imaging and multimodal models demonstrated comparatively promising performance on incidentally-detected nodules. However, when applied to nodules that underwent biopsy, all models underperformed. Conclusion: These results underscore the strengths and limitations of 8 validated predictive models and highlight promising directions towards personalized, noninvasive lung cancer diagnosis. © 2024, CC BY-NC-SA.

关键词： Biopsy

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Structural, optical, and thermal properties of BN thin films grown on diamond via pulsed laser deposition

arXiv

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arXiv 2023年

作者： Biswas, Abhijit Alvarez, Gustavo A. Li, Tao Christiansen-Salameh, Joyce Jeong, Eugene Puthirath, Anand B. Iyengar, Sathvik Ajay Li, Chenxi Gray, Tia Zhang, Xiang Pieshkov, Tymofii S. Kannan, Harikishan Elkins, Jacob Vajtai, Robert Birdwell, A. Glen Neupane, Mahesh R. Garratt, Elias J. Pate, Bradford B. Ivanov, Tony G. Zhao, Yuji Tian, Zhiting Ajayan, Pulickel M. Department of Materials Science and Nanoengineering Rice University HoustonTX77005 United States Sibley School of Mechanical and Aerospace Engineering Cornell University IthacaNY14853 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States DEVCOM Army Research Laboratory RF Devices and Circuits AdelphiMD20783 United States Naval Research Laboratory Chemistry Division WashingtonDC20375 United States

Heterostructures based on ultrawide-bandgap (UWBG) semiconductors (bandgap >4.0 eV), such as boron nitride (BN) and diamond, hold significant importance for the development of high-power electronics in the next generation. However, achieving in-situ hetero-epitaxy of BN/diamond or vice versa remains exceptionally challenging due to the complex growth kinetics involved. In this study, we have grown BN thin film on (100) single crystal diamonds using pulsed laser deposition and investigated its structural, magnetic, optical, and thermal properties. The structural analyses confirmed the growth of BN films, which exhibited diamagnetic behavior at room temperature. Notably, the film demonstrated anisotropic refractive index characteristics within the visible-to-near-infrared wavelength range. The room temperature cross-plane thermal conductivity of BN is 1.53 (± 0.77) W/mK, while the thermal conductance of the BN/diamond interface is 20 (± 2) MW/m2K. These findings have significant implications for a range of device applications based on UWBG BN/diamond heterostructures. © 2023, CC BY.

关键词： Diamonds

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At the Junction Between Deep Learning and Statistics of Extremes: Formalizing the Landslide Hazard Definition

Journal of Geophysical Research: Machine Learning and Comput...

引用

Journal of Geophysical Research: Machine Learning and Computation 2024年第3期1卷

作者： Ashok Dahal Raphaël Huser Luigi Lombardo Faculty of Geo-Information Science and Earth Observation (ITC) University of Twente Enschede The Netherlands Statistics Program Computer Electrical and Mathematical Sciences and Engineering (CEMSE) Division King Abdullah University of Science and Technology (KAUST) Thuwal Saudi Arabia

The most adopted definition of landslide hazard combines spatial information about landslide location (susceptibility), threat (intensity), and frequency (return period). Only the first two elements are usually considered and estimated when working over vast areas. Even then, separate models constitute the standard, with frequency being rarely investigated. Frequency and intensity are dependent on each other because larger events occur less frequently and vice versa. However, due to the lack of multi-temporal inventories and joint statistical models, modeling such properties via a unified hazard model has always been challenging and has yet to be attempted. Here, we develop a unified model to estimate landslide hazard at the slope unit level to address such gaps. We employed deep learning, combined with extreme-value theory to analyze an inventory of 30 years of observed rainfall-triggered landslides in Nepal and assess landslide hazard for multiple return periods. We also use our model to further explore landslide hazard for the same return periods under different climate change scenarios up to the end of the century. Our model performs excellently (with an accuracy of 0.78 and an area under the curve of 0.86) and can be used to model landslide hazard in a unified manner. Geomorphologically, we find that under climate change scenarios (SSP245 and SSP585), landslide hazard is likely to increase up to two times on average in the lower Himalayan regions (Siwalik and lower Himalayas; ≈110–3,500 m) while remaining the same in the middle Himalayan region (≈3,500–5,000 m) whilst decreasing slightly in the upper Himalayan region (≳5,000 m) areas. A Landslide hazard model is developed by combining deep learning and the extended generalized Pareto distribution from extreme value theory Thirty years of past observations are used to model the current landslide hazard scenario under different return periods of precipitation Landslide hazard is predicted for multiple return peri

关键词： landslides statistics of extremes deep learning climate change modeling Nepal

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Dish-Trend: Intervention Modeling Simulator That Accounts for Trend Influences

Dish-Trend: Intervention Modeling Simulator That Accounts fo...

引用

Simulation Winter Conference

作者： Stefan Andjelkovic Natasa Miskov-Zivanov Computational and Systems Biology Joint Carnegie Mellon University and University of Pittsburgh Computational Biology PhD Program University of Pittsburgh Pittsburgh PA USA Electrical and Computer Engineering Bioengineering Computational and Systems Biology University of Pittsburgh Pittsburgh PA USA

ISBN: (纸本)9781665433129

Simulation on directed graphs is an important method for understanding the dynamics in the systems where connectivity graphs contain cycles. Discrete Stochastic Heterogeneous Simulator (DiSH) is one of the simulation tools with wide application, which uses regulator values to calculate state updates of regulated elements. Here we present a new simulation approach DiSH-trend which also takes into account the trends in regulating elements. We demonstrate the features of trend-based regulation, as well as hybrid regulation, which is a combination of the trend- and level-based approaches. The modeling capabilities are demonstrated on a small toy model, showcasing different functionalities. Real-world capabilities are demonstrated on a larger network model of food insecurity in the Ethiopian region Oromia. Adding trend-based regulation to models results in increased modeling flexibility, and hybrid regulation improves qualitative dynamic behavior prediction. With appropriate data, DiSH-trend becomes a powerful tool for exploring intervention strategies.

关键词： Regulators Toy manufacturing industry Stochastic processes Predictive models Market research Regulation Data models

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Time-domain methods for quantifying dynamic cerebral blood flow autoregulation: Review and recommendations. A white paper from the Cerebrovascular Research Network (CARNet)

引用

Journal of Cerebral Blood Flow and Metabolism 2024年第9期44卷 1480-1514页

作者： Kostoglou, Kyriaki Bello-Robles, Felipe Brassard, Patrice Chacon, Max Claassen, Jurgen AHR Czosnyka, Marek Elting, Jan-Willem Hu, Kun Labrecque, Lawrence Liu, Jia Marmarelis, Vasilis Z Payne, Stephen J Shin, Dae Cheol Simpson, David Smirl, Jonathan Panerai, Ronney B Mitsis, Georgios D Department of Electrical and Computer Engineering McGill University Montreal QC Canada Institute of Neural Engineering Graz University of Technology Graz Austria Departamento de Ingeniería Informática Universidad de Santiago de Chile Santiago Chile Department of Kinesiology Faculty of Medicine Université Laval QC Canada Research Center of the Institut universitaire de cardiologie et de pneumologie de Québec Quebec QC Canada Department of Geriatrics Radboud University Medical Center Research Institute for Medical Innovation and Donders Institute Nijmegen Netherlands Cerebral Haemodynamics in Ageing and Stroke Medicine (CHiASM) Department of Cardiovascular Sciences University of Leicester Leicester United Kingdom Department of Clinical Neurosciences Neurosurgery Department University of Cambridge Cambridge United Kingdom Department of Neurology and Clinical Neurophysiology University Medical Center Groningen Groningen Netherlands Medical Biodynamics Program Division of Sleep and Circadian Disorders Brigham and Women's Hospital Harvard Medical School Boston MA United States Division of Sleep Medicine Harvard Medical School Boston MA United States Laboratory for Engineering and Scientific Computing Institute of Advanced Computing and Digital Engineering Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Shenzhen China Department Biomedical Engineering Viterbi School of Engineering University of Southern California Los Angeles CA United States Institute of Applied Mechanics National Taiwan University Taipei Taiwan Institute of Sound and Vibration Research University of Southampton Southampton United Kingdom Cerebrovascular Concussion Laboratory Faculty of Kinesiology University of Calgary Calgary AB Canada Sport Injury Prevention Research Centre Faculty of Kinesiology University of Calgary Calgary AB Canada Hotchkiss Brain Institute University of Calgary Calgary AB Canada NIHR Leicester Biomedical Research Centre Bri

Cerebral Autoregulation (CA) is an important physiological mechanism stabilizing cerebral blood flow (CBF) in response to changes in cerebral perfusion pressure (CPP). By maintaining an adequate, relatively constant supply of blood flow, CA plays a critical role in brain function. Quantifying CA under different physiological and pathological states is crucial for understanding its implications. This knowledge may serve as a foundation for informed clinical decision-making, particularly in cases where CA may become impaired. The quantification of CA functionality typically involves constructing models that capture the relationship between CPP (or arterial blood pressure) and experimental measures of CBF. Besides describing normal CA function, these models provide a means to detect possible deviations from the latter. In this context, a recent white paper from the Cerebrovascular Research Network focused on Transfer Function Analysis (TFA), which obtains frequency domain estimates of dynamic CA. In the present paper, we consider the use of time-domain techniques as an alternative approach. Due to their increased flexibility, time-domain methods enable the mitigation of measurement/physiological noise and the incorporation of nonlinearities and time variations in CA dynamics. Here, we provide practical recommendations and guidelines to support researchers and clinicians in effectively utilizing these techniques to study CA. © The Author(s) 2024.

关键词： CARNet cerebral autoregulation cerebral blood flow time-domain methods white paper

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