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arXiv 2021年

作者： Zhang, Yi Zong, Haonan Zong, Cheng Tan, Yuying Zhang, Meng Zhan, Yuewei Cheng, Ji-Xin Department of Physics Boston University BostonMA02215 United States Department of Electrical and Computer Engineering Boston University BostonMA02215 United States Department of Biomedical Engineering Boston University BostonMA02215 United States Photonics Center Boston University BostonMA02215 United States

Mid-infrared photothermal microscopy is a new chemical imaging technology in which a visible beam senses the photothermal effect induced by a pulsed infrared laser. This technology provides infrared spectroscopic information at sub-micron spatial resolution and enables infrared spectroscopy and imaging of living cells and organisms. Yet, current mid-infrared photothermal imaging sensitivity suffers from a weak dependance of scattering on temperature and the image quality is vulnerable to the speckles caused by scattering. Here, we present a novel version of mid-infrared photothermal microscopy in which thermo-sensitive fluorescent probes are harnessed to sense the mid-infrared photothermal effect. The fluorescence intensity can be modulated at the level of 1% per Kelvin, which is 100 times larger than the modulation of scattering intensity. In addition, fluorescence emission is free of speckles, thus much improving the image quality. Moreover, fluorophores can target specific organelles or biomolecules, thus augmenting the specificity of photothermal imaging. Spectral fidelity is confirmed through fingerprinting a single bacterium. Finally, the photobleaching issue is successfully addressed through the development of a wide-field fluorescence-enhanced mid-infrared photothermal microscope which allows video rate bond-selective imaging of biological specimens. © 2021, CC BY-NC-ND.

关键词： Infrared devices

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Progress in wearable electronics/photonics—Moving toward the era of artificial intelligence and internet of things

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InfoMat 2020年第6期2卷 1131-1162页

作者： Qiongfeng Shi Bowei Dong Tianyiyi He Zhongda Sun Jianxiong Zhu Zixuan Zhang Chengkuo Lee Department of Electrical and Computer Engineering National University of SingaporeSingapore117576Singapore Center for Intelligent Sensors and MEMS National University of SingaporeSingapore117608Singapore Hybrid-Integrated Flexible(Stretchable)Electronic Systems Program National University of SingaporeSingapore117608Singapore NUS Suzhou Research Institute(NUSRI) Suzhou215123China NUS Graduate School for Integrative Science and Engineering National University of SingaporeSingapore117456Singapore

The past few years have witnessed the significant impacts of wearable electronics/photonics on various aspects of our daily life,for example,healthcare monitoring and treatment,ambient monitoring,soft robotics,prosthetics,flexible display,communication,human-machine interactions,and so *** to the development in recent years,the next-generation wearable electronics and photonics are advancing rapidly toward the era of artificial intelligence(AI)and internet of things(IoT),to achieve a higher level of comfort,convenience,connection,and ***,this review provides an opportune overview of the recent progress in wearable electronics,photonics,and systems,in terms of emerging materials,transducing mechanisms,structural configurations,applications,and their further integration with other ***,development of general wearable electronics and photonics is summarized for the applications of physical sensing,chemical sensing,humanmachine interaction,display,communication,and so *** self-sustainable wearable electronics/photonics and systems are discussed based on system integration with energy harvesting and storage ***,technology fusion of wearable systems and AI is reviewed,showing the emergence and rapid development of intelligent/smart *** the last section of this review,perspectives about the future development trends of the next-generation wearable electronics/photonics are provided,that is,toward multifunctional,self-sustainable,and intelligent wearable systems in the AI/IoT era.

关键词： artificial intelligence energy harvesting human-machine interface internet of things wearable electronics wearable photonics

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Population stratification enables modeling effects of reopening policies on mortality and hospitalization rates

arXiv

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arXiv 2020年

作者： Huang, Tongtong Chu, Yan Shams, Shayan Kim, Yejin Allen, Genevera Annapragada, Ananth V. Subramanian, Devika Kakadiaris, Ioannis Gottlieb, Assaf Jiang, Xiaoqian School of Biomedical Informatics UTHealth HoustonTX United States Department of Computer Science & Electrical and Computer Engineering Rice University HoustonTX United States Department of Pediatric Radiology Texas Children’s hospital HoustonTX United States Department of Computer Science Electrical & Computer Engineering and Biomedical Engineering University of Houston HoustonTX United States

Objective: We study the influence of local reopening policies on the composition of the infectious population and their impact on future hospitalization and mortality rates. Materials and Methods: We collected datasets of daily reported hospitalization and cumulative morality of COVID-19 in Houston, Texas, from May 1, 2020 until June 29, 2020. These datasets are from multiple sources (USA FACTS, Southeast Texas Regional Advisory Council COVID-19 report, TMC daily news, and New York Times county-level mortality reporting). Our model, risk-stratified SIR-HCD uses separate variables to model the dynamics of local-contact (e.g., work from home) and high-contact (e.g., work on site) subpopulations while sharing parameters to control their respective R0(t) over time. Results: We evaluated our model’s forecasting performance in Harris County, TX (the most populated county in the Greater Houston area) during the Phase-I and Phase-II reopening. Not only did our model outperform other competing models, it also supports counterfactual analysis to simulate the impact of future policies in a local setting, which is unique among existing approaches. Discussion: Local mortality and hospitalization are significantly impacted by quarantine and reopening policies. No existing model has directly accounted for the effect of these policies on local trends in infections, hospitalizations, and deaths in an explicit and explainable manner. Our work is an attempt to close this important technical gap to support decision making. Conclusion: Despite several limitations, we think it is a timely effort to rethink about how to best model the dynamics of pandemics under the influence of reopening policies. Copyright © 2020, The Authors. All rights reserved.

关键词： Hospitals

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High-Resolution Three-Dimensional Hybrid MRI + Low Dose CT Vocal Tract Modeling: A Cadaveric Pilot Study

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Journal of Voice 2022年

作者： MEYER, David RUSHO, Rushdi Zahid ALAM, Wahidul CHRISTENSEN, Gary E. HOWARD, David M. ATHA, Jarron HOFFMAN, Eric A. STORY, Brad TITZE, Ingo R. LINGALA, Sajan Goud Janette Ogg Voice Research Center Shenandoah University Winchester Virginia United States Roy J Carver Department of Biomedical Engineering University of Iowa Iowa City Iowa United States Department of Electrical and Computer Engineering University of Iowa Iowa City Iowa United States Department of Electronic Engineering Royal Holloway University of London LDN United Kingdom Departments of Radiology Medicine and Roy J Carver Department of Biomedical Engineering University of Iowa Iowa City Iowa United States College of Science University of Arizona Tucson AZ United States Utah Center for Vocology The University of Utah Salt Lake City UT United States

Objectives: MRI based vocal tract models have many applications in voice research and education. These models do not adequately capture bony structures (e.g. teeth, mandible), and spatial resolution is often relatively low in order to minimize scanning time. Most MRI sequences achieve 3D vocal tract coverage at gross resolutions of 2 mm³ within a scan time of <20 seconds. Computed tomography (CT) is well suited for vocal tract imaging, but is infrequently used due to the risk of ionizing radiation. In this cadaveric study, a single, extremely low-dose CT scan of the bony structures is blended with accelerated high-resolution (1 mm³) MRI scans of the soft tissues, creating a high-resolution hybrid CT-MRI vocal tract model. Methods: Minimum CT dosages were determined and a custom 16-channel airway receiver coil for accelerated high (1 mm³) resolution MRI was evaluated. A rigid body landmark based partial volume registration scheme was then applied to the images, creating a hybrid CT-MRI model that was segmented in Slicer. Results: Ultra-low dose CT produced images with sufficient quality to clearly visualize the bone, and exposed the cadaver to 0.06 mSv. This is comparable to atmospheric exposures during a round trip transatlantic flight. The custom 16-channel vocal tract coil produced acceptable image quality at 1 mm³ resolution when reconstructed from ∼6 fold undersampled data. High (1 mm³) resolution MR imaging of short (<10 seconds) sustained sounds was achieved. The feasibility of hybrid CT-MRI vocal tract modeling was successfully demonstrated using the rigid body landmark based partial volume registration scheme. Segmentations of CT and hybrid CT-MRI images provided more detailed 3D representations of the vocal tract than 2 mm³ MRI based segmentations. Conclusions: The method described in this study indicates that high-resolution CT and MR image sets can be combined so that structures such as tee

关键词： Airway Computed Tomography(CT) Magnetic Resonance Imaging(MRI) Modeling Segmentation Vocal tract

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Assessing Dynamic Cerebral Autoregulation in Patients with Sickle Cell Disease Using Near-Infrared Spectroscopy and Paced Breathing

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BLOOD 2020年 136卷 57-58页

作者： Wood, Sossena Fanta, Abeselom Dosunmu-Ogunbi, Atinuke Ruesch, Alexander Jonassaint, Jude Huppert, Theodore Novelli, Enrico M. Kainerstorfer, Jana Department of Biomedical Engineering Carnegie Mellon University Pittsburgh PA Carnegie Mellon Neuroscience Institute Carnegie Mellon University Pittsburgh PA University of Pittsburgh School of Medicine Pittsburgh PA Academic Research Center for Hematology (ARCH) University of Pittsburgh Pittsburgh PA Department of Electrical and Computer Engineering University of Pittsburgh Pittsburgh PA Heart Lung and Blood Vascular Medicine Institute University of Pittsburgh Pittsburgh PA

Introduction. Sickle cell disease (SCD) is caused by hemoglobin S polymerization leading to vaso-occlusion, small vessel disease, and reduced tissue oxygen saturation. Noninvasive assessments and screening of small vessel disease and decreased oxygen saturation in select organs, like the brain, are poorly developed. Cerebral autoregulation, a mechanism that ensures cerebral blood flow (CBF) remains constant with changes in mean arterial pressure, is impaired with and is a marker of small vessel disease. Frequency-domain near-infrared spectroscopy (FD-NIRS) can be used as a noninvasive technique to measure cerebral autoregulation by recording cerebral microvascular changes in hemoglobin concentration that are related to cerebral blood flow. Transfer function analysis is a method to noninvasively quantify the relationship between measured physiologic signals, and can be used to estimate cerebral autoregulation. In this study, we hypothesized patients with SCD have impaired cerebral autoregulation and reduced tissue oxygen saturation, which we evaluated via FD-NIRS with transfer function analysis, as compared to healthy controls. Methods. All patients provided informed consent under an IRB protocol approved by the University of Pittsburgh and Carnegie Mellon University. Patients with SCD (n = 11) and healthy, race-matched controls (n =14) were enrolled. All participants sat upright in a chair with probes of a commercial multi-distance FD-NIRS apparatus applied to their forehead in a dark room (Fig. 1A). We used paced breathing to dynamically induce controlled changes in the microvascular tone at 0.1, 0.125, and 0.1667 Hz, spanning normal to more challenging breathing rates, with a visual metronome guiding each paced breathing session (Fig.1.B). To validate each breathing pace, we recorded the participants’ respiratory rate via a belt placed around their chest, and their mean arterial pressure through a finger and arm cuff attached to a beat-to-beat finger plethysmograp

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Deep Automatic Alignment of Mpox Dermatological Hand Photography

Deep Automatic Alignment of Mpox Dermatological Hand Photogr...

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IEEE International Symposium on biomedical Imaging

作者： Bohan Jiang Andrew McNeil Yihao Liu Gaurav Rudravaram Inga Saknite Placide Mbala-Kingebeni Olivier Tshiani Mbaya Tyra Silaphet Rachel Weiss Lori E. Dodd Veronique Nussenblatt Daniel Moyer Bennett A. Landman Benoit M. Dawant Eric R. Tkaczyk Department of Electrical and Computer Engineering Vanderbilt University Nashville TN USA Department of Dermatology Vanderbilt University Medical Center Nashville TN USA Department of Veterans Affairs Dermatology Service and Research Service Nashville TN USA Biophotonics Laboratory University of Latvia Riga Latvia Institut National de Recherche Biomedicale Kinshasa Democratic Republic of the Congo Clinical Monitoring Research Program Directorate Frederick National Laboratory for Cancer Research Frederick MD USA Clinical Trials Research Section Division of Clinical Research National Institute of Allergy and Infectious Disease Bethesda MD USA Laboratory of Clinical Immunology and Microbiology National Institute of Allergy and Infectious Diseases Bethesda MD USA Department of Computer Science Vanderbilt University Nashville TN USA

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

Mpox is a viral illness with heavy cutaneous involvement. Automatic tracking of mpox lesion progression is critical in determining the resolution of evolving lesions. This work introduces a novel application of deep learning for lesion monitoring through alignment of dermatological hand photographs. By adapting the VoxelMorph framework for 2D photographic data, we explore key point alignment across serial images. We trained our neural network model on a unique dataset of 1,658 hand images and evaluated its performance on a test set of 254 images. Additionally, we validated the method's generalizability with a supplementary set of 500 images, which included extensive Mpox infection. Our findings indicate modest yet significant improvements in key points and lesion center registration across different regularization strengths. Although promising, the complexity of hand structure presents challenges, requiring cautious application and further refinement, especially in regions with intense spatial discontinuities, such as interdigital areas.

关键词： Hands Photography Deep learning Training Three-dimensional displays Image resolution Neural networks Parametric statistics Lesions Monitoring

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Compressibility-Near-Zero Acoustic Radiation

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Physical Review Applied 2021年第2期15卷 024022-024022页

作者： Curtis Rasmussen Andrea Alù Department of Mechanical Engineering The University of Texas at Austin Austin Texas 78712 USA Department of Electrical and Computer Engineering The University of Texas at Austin Austin Texas 78712 USA Photonics Initiative CUNY Advanced Science Research Center New York New York 10031 USA Physics Program Graduate Center City University of New York New York New York 10026 USA

A hallmark of near-zero-index materials is the uniform phase profile that the waves experience as they propagate with staticlike properties in these media. This feature is exploited in electromagnetics for several applications, including for the realization of compact highly directive antennas illuminated by a single source. Here, we discuss the promise of near-zero metamaterials for acoustic radiation, based on the cutoff of a higher-order mode in a waveguide with small holes. We show that the near-zero nature of this phenomenon ensures unusual robustness to disorder, which is analyzed using a statistical description of the radiation patterns for randomly generated location of the holes. The radiation pattern can be made more directive by simply increasing the overall radiating aperture, without having to worry about the specific location of individual holes and their relative distance. The proposed zero-compressibility material offers a promising alternative to traditional acoustic directive sources due to its design simplicity, inherent robustness, and compact profile.

关键词： Acoustic metamaterials Acoustic wave phenomena Disordered systems Acoustic techniques Cavity resonators Green's function methods

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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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Epipolar Geometry on Drones Cameras for Swarm Robotics Applications

Epipolar Geometry on Drones Cameras for Swarm Robotics Appli...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Andres Erazo Eduardo Tayupanta Seok-Bum Ko Division of Biomedical Engineering University of Saskatchewan Member IEEE Saskatoon Canada Department of Electrical and Electronic Engineering Universidad de las Fuerzas Armadas − ESPE Quito Ecuador Department of Electrical and Computer Engineering and Division of Biomedical Engineering University of Saskatchewan Senior Member IEEE Saskatoon Canada

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

Nowadays, Convolutional Neural Networks are commonly used in classification of images due to their accuracy and performance. In robotics, cameras are used as the main sensor to be able to gather information of the environment; however, image processing could require great amounts of resources. An approach for object detection for 3D environment navigation was implemented, using onboard 2D cameras of mini-drones. A TensorFlow network was fine-tuned for specific object classification and epipolar geometry used to obtain measures of distance between three drones and the detected items. An average measurement accuracy of 0.6094 was obtained, with an average projection error of the cameras of 0.08779. The processing time for object prediction was approximately 0.02 seconds, which correspond to the 37% of the total time needed for a Node's iteration.

关键词： Cameras Drones Robots Optical distortion Three-dimensional displays Image reconstruction IP networks

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Idealized aortic annuloplasty FSI digital twin of 3D-printed phantoms with 4D-flow MRI comparison

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computers in Biology and Medicine 2025年第Pt B期192卷 110398-110398页

作者： Bontempi, Luca Zattoni, Marta Ramella, Anna Migliavacca, Francesco Ringgaard, Steffen Kim, Won Yong Johansen, Peter Colombo, Monika Department of Mechanical and Production Engineering Aarhus University Aarhus Denmark Department of Chemistry Materials and Chemical Engineering "Giulio Natta" Politecnico di Milano Milan Italy Department of Biomedical Engineering Thoraxcenter Erasmus MC Rotterdam Netherlands Department of Clinical Medicine Aarhus University Denmark Department of MR Research Centre Aarhus University Hospital Denmark Department of Cardiology Aarhus University Hospital Denmark Department of Electrical and Computer Engineering Aarhus University Denmark Department of Cardiothoracic and Vascular Surgery Aarhus University Hospital Denmark

Background: Aortic annuloplasty, involving the implantation of an external ring around the aortic root to reduce annular dimensions, is a promising treatment for aortic valve insufficiency. However, its hemodynamic effects remain underexplored due to the absence of computational models validated by experimental and clinical data. Methods: This study introduces a computational fluid-structure interaction (FSI) model of supra valvular aortic annuloplasty using 4D-flow magnetic resonance imaging (MRI). Native and post-annuloplasty conditions of idealized aortic root phantoms, including the aortic valve, were CAD-modelled and 3D-printed with elastic resin. These phantoms were tested in a mock circulatory flow-loop providing normal pulsatile physiologic conditions using a glycerol-water mixture to simulate blood viscosity. Flow and pressure data collected from sensors were used as boundary conditions for FSI simulations. Experimental velocity fields from 4D-flow MRI were compared to computational results to assess model accuracy. Results: MRI scans of the annuloplasty model showed an increased peak systolic velocity (up to 145.4 cm/s) and localized flow alterations, corresponding to a higher pressure gradient across the valve. During regurgitation, the annuloplasty model showed broader velocity distributions compared to the native condition. The FSI simulations closely matched 4D-flow MRI data, with strong correlation coefficients (r > 0.93) and minimal Bland-Altman differences, particularly during systolic phases. Conclusions: This study establishes an integrative methodology combining in-vitro, in-silico, and clinical imaging techniques to evaluate aortic annuloplasty hemodynamics. The in-vitro validated digital twin framework offers a pathway for patient-specific modelling, enabling prediction of surgical outcomes and optimization of aortic valve repair strategies. © 2025 The Authors

关键词： Theranostics

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