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arXiv 2024年

作者： Venkatesan, Balaji Guan, Syu-You Chang, Jen-Te Chiu, Shiang-Bin Yang, Po-Yuan Su, Chih-Chuan Chang, Tay-Rong Raju, Kalaivanan Sankar, Raman Fongchaiya, Somboon Chu, Ming-Wen Chang, Chia-Seng Chang, Guoqing Lin, Hsin Del Maestro, Adrian Kao, Ying-Jer Chuang, Tien-Ming Department of Physics National Taiwan University Taipei10617 Taiwan Nano Science and Technology Program Taiwan International Graduate Program Academia Sinica National Taiwan University Taipei11529 Taiwan Institute of Physics Academia Sinica Taipei11529 Taiwan Department of Physics National Cheng-Kung University Tainan701 Taiwan Center for Condensed Matter Sciences National Taiwan University Taipei10617 Taiwan Molecular Science and Technology Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University 21 Nanyang Link 637371 Singapore Department of Physics and Astronomy University of Tennessee KnoxvilleTN37996 United States Institute for Advanced Materials & Manufacturing University of Tennessee KnoxvilleTN37996 United States Min H. Kao Department of Electrical Engineering and Computer Science University of Tennessee KnoxvilleTN37996 United States Center for Quantum Science and Technology National Taiwan University Taipei10607 Taiwan

Electronic liquid crystal (ELC) phases are spontaneous symmetry breaking states believed to arise from strong electron correlation in quantum materials such as cuprates and iron pnictides. Here, we report a direct observation of a smectic phase in a weakly correlated Dirac nodal line (DNL) semimetal GdSbxTe2-x. Incommensurate smectic charge modulation and intense local unidirectional nanostructure are visualized by using spectroscopic imaging - scanning tunneling microscopy. As topological materials with symmetry protected Dirac or Weyl fermions are mostly weakly correlated, the discovery of such an ELC phase are anomalous and raise questions on the origin of their emergence. Specifically, we demonstrate how chemical substitution generates these symmetry breaking phases before the system undergoes a charge density wave (CDW) - orthorhombic structural transition. Our results highlight the importance of impurities in realizing ELC phases and present a new material platform for exploring the interplay among quenched disorder, topology and electron correlation. Copyright © 2024, The Authors. All rights reserved.

关键词： Charge density waves

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Nanoplasmonic microbubble and nanoplasmonic sensing – Two birds in one stone

Nanoplasmonic microbubble and nanoplasmonic sensing – Two b...

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Optical Sensors, Sensors 2020 - Part of Optical Sensors and Sensing Congress 2020

作者： Ohannesian, Nareg Misbah, Ibrahim Shih, Wei-Chuan Department of Electrical and Computer Engineering University of Houston 4800 Calhoun Rd HoustonTX77004 United States Department of Biomedical Engineering University of Houston 4800 Calhoun Rd HoustonTX77004 United States Program of Materials Science and Engineering University of Houston 4800 Calhoun Rd HoustonTX77004 United States Department of Chemistry University of Houston 4800 Calhoun Rd HoustonTX77004 United States

ISBN: (纸本)9781557528209

We present low power operated nanoplasmonic microbubble generation using near infrared light for particle concentrating on high-density arrayed nanoporous gold disks. Utilizing a spatial light modulator provides precise control of size and location of multiple microbubbles. After concentrating, various nanoplasmonic sensing techniques can be directly performed. © OSA 2020.

关键词： Infrared devices

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Identifying Materials-Level Sources of Performance Variation in Superconducting Transmon Qubits

arXiv

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arXiv 2025年

作者： Murthy, Akshay A. Bal, Mustafa Bedzyk, Michael J. Cansizoglu, Hilal Chan, Randall K. Chandrasekhar, Venkat Crisa, Francesco Datta, Amlan Deng, Yanpei Matute Diaz, Celeo D. Dravid, Vinayak P. Garcia-Wetten, David A. Garattoni, Sabrina Ghimire, Sunil Goronzy, Dominic P. de Graaf, Sebastian E. Haeuser, Sam Hersam, Mark C. Isheim, Dieter Joshi, Kamal Kim, Richard Kolachina, Saagar Kopas, Cameron J. Kramer, Matthew J. Lachman, Ella O. Lee, Jaeyel Lim, Peter G. Lunin, Andrei Mah, William Marshall, Jayss Mutus, Josh Y. Oh, Jin-Su Pappas, David P. Park, Joong-Mok Prozorov, Ruslan dos Reis, Roberto Seidman, David N. Sung, Zuhawn Tanatar, Makariy Walker, Mitchell J. Wang, Jigang Wu, Haotian Zhou, Lin Zhu, Shaojiang Grassellino, Anna Romanenko, Alexander BataviaIL60510 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Rigetti Computing BerkeleyCA94710 United States Ames National Laboratory AmesIA50011 United States Department of Physics & Astronomy Iowa State University AmesIA50011 United States Department of Physics and Astronomy Northwestern University EvanstonIL60208 United States The NUANCE Center Northwestern University EvanstonIL60208 United States International Institute of Nanotechnology Northwestern University EvanstonIL60208 United States National Physical Laboratory TeddingtonTW11 0LW United Kingdom Department of Chemistry Northwestern University EvanstonIL60208 United States Department of Electrical and Computer Engineering Northwestern University EvanstonIL60208 United States Applied Physics Graduate Program Northwestern University EvanstonIL60208 United States Department of Materials Science and Engineering Iowa State University AmesIA50011 United States

The Superconducting Materials and Systems (SQMS) Center, a DOE National Quantum Information Science Research Center, has conducted a comprehensive and coordinated study using superconducting transmon qubit chips with known performance metrics to identify the underlying materials-level sources of device-to-device performance variation. Following qubit coherence measurements, these qubits of varying base superconducting metals and substrates have been examined with various nondestructive and invasive material characterization techniques at Northwestern University, Ames National Laboratory, and Fermilab as part of a blind study. We find trends in variations of the depth of the etched substrate trench, the thickness of the surface oxide, and the geometry of the sidewall, which when combined, lead to correlations with the T1 lifetime across different devices. In addition, we provide a list of features that varied from device to device, for which the impact on performance requires further studies. Finally, we identify two low-temperature characterization techniques that may potentially serve as proxy tools for qubit measurements. These insights provide materials-oriented solutions to not only reduce performance variations across neighboring devices, but also to engineer and fabricate devices with optimal geometries to achieve performance metrics beyond the state-of-the-art values. © 2025, CC BY.

关键词： Qubits

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Clinical characteristics of hospitalized children with community-acquired pneumonia and respiratory infections: Using machine learning approaches to support pathogen prediction at admission

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Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi 2023年第4期56卷 772-781页

作者： Tu-Hsuan Chang Yun-Chung Liu Siang-Rong Lin Pei-Hsin Chiu Chia-Ching Chou Luan-Yin Chang Fei-Pei Lai Department of Pediatrics Chi Mei Medical Center Tainan City Taiwan. Department of Pediatrics National Taiwan University Hospital College of Medicine National Taiwan University Taipei City Taiwan. Institute of Applied Mechanics National Taiwan University Taipei City Taiwan. Institute of Applied Mechanics National Taiwan University Taipei City Taiwan. Electronic address: ccchou@iam.ntu.edu.tw. Department of Pediatrics National Taiwan University Hospital College of Medicine National Taiwan University Taipei City Taiwan. Electronic address: lychang@ntu.edu.tw. Graduate Institute of Biomedical Electronics and Bioinformatics Taipei City National Taiwan University Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei City Taiwan Department of Electrical Engineering National Taiwan University Taipei City Taiwan.

BACKGROUND:Acute respiratory infections (ARIs) are common in children. We developed machine learning models to predict pediatric ARI pathogens at admission. METHODS:We included hospitalized children with respiratory infections between 2010 and 2018. Clinical features were collected within 24 h of admission to construct models. The outcome of interest was the prediction of 6 common respiratory pathogens, including adenovirus, influenza virus types A and B, parainfluenza virus (PIV), respiratory syncytial virus (RSV), and Mycoplasma pneumoniae (MP). Model performance was estimated using area under the receiver operating characteristic curve (AUROC). Feature importance was measured using Shapley Additive exPlanation (SHAP) values. RESULTS:A total of 12,694 admissions were included. Models trained with 9 features (age, event pattern, fever, C-reactive protein, white blood cell count, platelet count, lymphocyte ratio, peak temperature, peak heart rate) achieved the best performance (AUROC: MP 0.87, 95% CI 0.83-0.90; RSV 0.84, 95% CI 0.82-0.86; adenovirus 0.81, 95% CI 0.77-0.84; influenza A 0.77, 95% CI 0.73-0.80; influenza B 0.70, 95% CI 0.65-0.75; PIV 0.73, 95% CI 0.69-0.77). Age was the most important feature to predict MP, RSV and PIV infections. Event patterns were useful for influenza virus prediction, and C-reactive protein had the highest SHAP value for adenovirus infections. CONCLUSION:We demonstrate how artificial intelligence can assist clinicians identify potential pathogens associated with pediatric ARIs upon admission. Our models provide explainable results that could help optimize the use of diagnostic testing. Integrating our models into clinical workflows may lead to improved patient outcomes and reduce unnecessary medical costs.

关键词： Children Community-acquired pneumonia Machine learning Pathogens prediction Respiratory infections

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Development of a Selective Wet-Chemical Etchant for 3D Structuring of Silicon via Nonlinear Laser Lithography

arXiv

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arXiv 2023年

作者： Borra, Mona Zolfaghari Radfar, Behrad Nasser, Hisham Çolakoğlu, Tahir Tokel, Onur Turnalı, Ahmet Demirtaş, Merve Ustunel, Hande Toffoli, Daniele Ömer İlday, F. Turan, Raşit Pavlov, Ihor Bek, Alpan ODTÜ-GÜNAM Middle East Technical University Ankara06800 Turkey Ankara06800 Turkey Department of Electronics and Nanoengineering Aalto University Tietotie 3 EspooFI-02150 Finland Department of Physics Engineering Ankara University Ankara06100 Turkey Department of Physics Bilkent University Ankara06800 Turkey UNAM National Nanotechnology Research Center Institute of Materials Science and Nanotechnology Bilkent University Ankara06800 Turkey Department of Electrical and Electronics Engineering Bilkent University Ankara06800 Turkey Department of Electrical and Computer Engineering Boston University 8 Saint Mary’s Street BostonMA02215 United States Ankara06800 Turkey Network Technologies Department TUBITAK ULAKBIM Ankara06800 Turkey Department of Chemical and Pharmaceutical Sciences Trieste University Trieste Italy IOM-CNR Istituto Officina dei Materiali Trieste34149 Italy Micro and Nanotechnology Graduate Program of Natural and Applied Sciences Middle East Technical Turkey

Recently-demonstrated high-quality three-dimensional (3D) subsurface laser processing inside crystalline silicon (c-Si) wafers opens a door to a wide range of novel applications in multidisciplinary research areas. Using this technique, a novel maskless micro-pillars with precise control on the surface reflection and coverage are successfully fabricated by etching the laser processed region of c-Si wafer. To achieve this, a particular selective wet chemical etching is developed to follow subsurface laser processing of c-Si to reveal the desired 3D structures with smooth surfaces. Here, we report the development of a novel chromium-free chemical etching recipe based on copper nitrate, which yields substantially smooth surfaces at high etch rate and selectivity on the both laser-processed Si surface and subsurface, i.e., without significant etching of the unmodified Si. Our results show that the etch rate and surface morphology are interrelated and strongly influenced by the composition of the adopted etching solution. After an extensive compositional study performed at room temperature, we identify an etchant with a selectivity of over 1600 times for laser-modified Si with respect to unmodified Si. We also support our findings using density functional theory calculations of HF and Cu adsorption energies, indicating significant diversity on the c-Si and laser-modified surfaces. Copyright © 2023, The Authors. All rights reserved.

关键词： Morphology

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Internet of Things in disaster management systems: A systematic review

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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.

关键词：

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Generalizability of splint therapy for temporomandibular joint disorders in the era of precision medicine

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International journal of rheumatic diseases 2023年第1期26卷 170-171页

作者： Shu-Hao Hsu Wei-Wei Liu Yung-Heng Lee Kevin Sheng-Kai Ma School of Medicine Chung Shan Medical University Taichung Taiwan Republic of China. Department of Orthopedics Cishan Hospital Ministry of Health and Welfare Kaohsiung Taiwan Republic of China. Center for Global Health Perelman School of Medicine University of Pennsylvania Philadelphia Pennsylvania USA. Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University Taipei Taiwan Republic of China. Department of Epidemiology Harvard T.H. Chan School of Public Health Boston Massachusetts USA. Department of Dermatology Massachusetts General Hospital Boston Massachusetts USA.

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3D-Printed electrochemical sensor-integrated transwell systems

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Microsystems & Nanoengineering 2020年第1期6卷 357-368页

作者： Pradeep Ramiah Rajasekaran Ashley Augustiny Chapin David N.Quan Jens Herberholz William E.Bentley Reza Ghodssi Institute for Systems Research University of MarylandCollege ParkMDUSA Fischell Department of Bioengineering University of MarylandCollege ParkMDUSA Department of Psychology and Neuroscience and Cognitive Science Program University of MarylandCollege ParkMDUSA Institute for Bioscience and Biotechnology Research University of MarylandCollege ParkMDUSA Robert E.Fischell Institute for Biomedical Devices University of MarylandCollege ParkMDUSA Department of Electrical and Computer Engineering University of MarylandCollege ParkMDUSA

This work presents a 3D-printed,modular,electrochemical sensor-integrated transwell system for monitoring cellular and molecular events in situ without sample extraction or microfluidics-assisted downstream *** additive manufacturing techniques such as 3D printing,shadow masking,and molding are used to fabricate this modular system,which is autoclavable,biocompatible,and designed to operate following standard operating protocols(SOPs)of cellular *** to the platform is a flexible porous membrane,which is used as a cell culture substrate similarly to a commercial transwell *** electrochemical sensors fabricated on the membrane allow direct access to cells and their products.A pair of gold electrodes on the top side of the membrane measures impedance over the course of cell attachment and growth,characterized by an exponential decrease(~160%at 10Hz)due to an increase in the double layer capacitance from secreted extracellular matrix(ECM)*** voltammetry(CV)sensor electrodes,fabricated on the bottom side of the membrane,enable sensing of molecular release at the site of cell culture without the need for downstream ***-time detection of ferrocene dimethanol injection across the membrane showed a three order-of-magnitude higher signal at the membrane than in the bulk media after reaching *** modular sensor-integrated transwell system allows unprecedented direct,real-time,and noninvasive access to physical and biochemical information,which cannot be obtained in a conventional transwell system.

关键词： transwell electrochemical culture

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Ultrastrong Spin-Photon Coupling in Gadolinium Gallium Garnet

Ultrastrong Spin-Photon Coupling in Gadolinium Gallium Garne...

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Conference on Lasers and Electro-Optics (CLEO)

作者： T. Elijah Kritzell Junzhe Bao Jacques Doumani Jae Joon Lee Hongjing Xu Fuyang Tay Hiroyuki Nojiri Motoaki Bamba Andrey Baydin Junichiro Kono Department of Electrical and Computer Engineering Rice University Houston Texas USA Applied Physics Graduate Program Smalley-Curl Institute Rice University Houston Texas USA Department of Physics and Astronomy Rice University Houston Texas USA Institute for Materials Research Tohoku University Senai Japan The Hakubi Center for Advanced Research Kyoto University Kyoto Japan Department of Physics I Kyoto University Kyoto Japan Smalley-Curl Institute Rice University Houston Texas USA Department of Material Science and NanoEngineering Rice University Houston Texas USA

We examine ultrastrong coupling of an ensemble of paramagnetic spins in Gd 3 Ga 5 O 12 with terahertz photons in the presence of a high external magnetic field both in the bulk and thin-film limits.

ISBN: (纸本)9781957171258

We examine ultrastrong coupling of an ensemble of paramagnetic spins in Gd 3 Ga 5 O 12 with terahertz photons in the presence of a high external magnetic field both in the bulk and thin-film limits.

关键词： CCD cameras Condensed matter Magnetic fields Photons Quantum optics Terahertz spectroscopy

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Data-driven Nucleus Subclassification on Colon H&E using Style-transferred Digital Pathology

arXiv

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arXiv 2024年

作者： Remedios, Lucas W. Bao, Shunxing Remedios, Samuel W. Lee, Ho Hin Cai, Leon Y. Li, Thomas Deng, Ruining Newlin, Nancy R. Saunders, Adam M. Cui, Can Li, Jia Liu, Qi Lau, Ken S. Roland, Joseph T. Washington, Mary K. Coburn, Lori A. Wilson, Keith T. Huo, Yuankai Landman, Bennett A. Vanderbilt University Department of Computer Science Nashville United States Vanderbilt University Department of Electrical and Computer Engineering Nashville United States Johns Hopkins University Department of Computer Science Baltimore United States National Institutes of Health Department of Radiology and Imaging Sciences Bethesda United States Vanderbilt University Department of Biomedical Engineering Nashville United States Vanderbilt University Medical Center Department of Biostatistics Nashville United States Vanderbilt University Medical Center Center for Quantitative Sciences Nashville United States Vanderbilt University Medical Center Epithelial Biology Center Nashville United States Vanderbilt University School of Medicine Department of Cell and Developmental Biology Nashville United States Vanderbilt University Medical Center Division of Gastroenterology Hepatology and Nutrition Department of Medicine Nashville United States Vanderbilt University Medical Center Vanderbilt Center for Mucosal Inflammation and Cancer Nashville United States Vanderbilt University School of Medicine Program in Cancer Biology Nashville United States Veterans Affairs Tennessee Valley Healthcare System NashvilleTN United States Vanderbilt University Medical Center Department of Pathology Microbiology and Immunology NashvilleTN United States

Purpose: Cells are building blocks for human physiology;consequently, understanding the way cells communicate, co-locate, and interrelate is essential to furthering our understanding of how the body functions in both health and disease. Hematoxylin and eosin (H&E) is the standard stain used in histological analysis of tissues. Microscope slides of H&E-stained tissues are widely available in both clinical and research settings. While H&E is ubiquitous and reveals tissue microanatomy, the classification and tracking of cell subtypes often requires expert knowledge and the use of specialized stains, such as immunofluorescence staining. To reduce both the manual annotation burden and reliance on specialized staining technologies, artificial intelligence has been proposed for the automatic classification of cell types on H&E slides. For example, the recent Colon Nucleus Identification and Classification (CoNIC) Challenge focused on labeling 6 cell types on imaging of H&E stains from the human colon. However, this is a very small fraction of the number of potential cell subtypes within the intestines. Specifically, the CoNIC Challenge was unable to classify epithelial subtypes (progenitor, enteroendocrine, goblet), lymphocyte subtypes (B, helper T, cytotoxic T), and connective subtypes (fibroblasts). To approach this problem, we propose to use inter-modality learning to label previously un-labelable cell types on H&E. Approach: We take advantage of the cell classification information inherent in whole slide images (WSIs) of multiplexed immunofluorescence (MxIF) histology to create cell level annotations for 14 subclasses. We performed style transfer on the same MxIF tissues to synthesize realistic virtual H&E which we paired with the MxIF-derived cell subclassification labels. We evaluated the efficacy of using a supervised learning scheme where the input was realistic-quality virtual H&E and the labels were MxIF-derived cell subclasses. We assessed our model on a testing

关键词： Tissue

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