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Spin scattering and Hall effects in monolayer Fe3GeTe2

Physical Review B 2023年第13期108卷 134425-134425页

作者： Luyan Yu Jie-Xiang Yu Jiadong Zang Roger K. Lake Houlong Zhuang Gen Yin Department of Physics University of Texas at Austin Austin Texas 78712 USA Department of Physics University of Florida Gainesville Florida 32611 USA Department of Physics and Materials Science Program University of New Hampshire Durham New Hampshire 03824 USA Laboratory for Terahertz and Terascale Electronics (LATTE) Department of Electrical and Computer Engineering University of California at Riverside Riverside California 92521 USA Mechanical and Aerospace Engineering Arizona State University Tempe Arizona 85287 USA Department of Physics Georgetown University Washington DC 20057 USA

We theoretically show that the carrier transport in a monolayer Fe3GeTe2 experiences a transition between anomalous and spin Hall effects when the spin polarization of disorders switches between out-of-plane and in-plane. These Hall effects are allowed when the magnetization is polarized in-plane, breaking the C3 rotation symmetry. The transition originates from the selection rule of spin scattering, the strong spin-orbit coupling, and the van Hove singularities near the Fermi surface. The scattering selection rule tolerates the sign change of the disorder spin, which provides a convenient method to detect the switching of antiferromagnetic insulators regardless of the interfacial roughness in a heterostructure. This provides a convenient platform for the study of 2D spintronics through various van der Waals heterostructures.

关键词： Magnetotransport Spin Hall effect 2-dimensional systems Density functional calculations

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Cantilever Actuator Module for on-Command Drug Deployment from Ingestible Capsules

Cantilever Actuator Module for on-Command Drug Deployment fr...

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International Conference on Solid State Sensors and Actuators (TRANSDUCERS)

作者： Joshua A. Levy Michael A. Straker Luke A. Beardslee Reza Ghodssi Department of Materials Science and Engineering University of Maryland College Park Maryland USA Institute for Systems Research University of Maryland College Park Maryland USA Robert E. Fischell Institute for Biomedical Devices University of Maryland College Park Maryland USA Fischell Department of Bioengineering University of Maryland College Park Maryland USA Department of Electrical and Computer Engineering University of Maryland College Park Maryland USA

This manuscript demonstrates the first cantilever actuator for highly targeted and directionally specific delivery of drug-eluting microneedles to the gastrointestinal (GI) tract from ingestible devices. The actuator achieves the following advantages over current technology: on-command deployment in under 500 ms, low power consumption, spatial conservation, and prolonged deployment shelf life. These advancements enable integration of multiple actuators per device for multidirectional deployment. These attributes are achieved by the optimization of heater design and use of low-profile and highly relaxation resistant PEEK polymers. In all, these features enable higher delivery precision in both longitudinal and polar directions, potentiating site targeting in the GI tract.

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Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue

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Light(science & Applications) 2020年第1期9卷 1273-1285页

作者： Yijie Zhang Kevin de Haan Yair Rivenson Jingxi Li Apostolos Delis Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Bioengineering Department University of CaliforniaLos AngelesCA 90095USA California NanoSystems Institute(CNSI) University of CaliforniaLos AngelesCA 90095USA Department of Computer Science University of CaliforniaLos AngelesCA 90095USA Department of Surgery David Geffen School of MedicineUniversity of CaliforniaLos AngelesCA 90095USA

Histological staining is a vital step in diagnosing various diseases and has been used for more than a century to provide contrast in tissue sections,rendering the tissue constituents visible for microscopic analysis by medical ***,this process is time consuming,labour intensive,expensive and destructive to the ***,the ability to virtually stain unlabelled tissue sections,entirely avoiding the histochemical staining step,has been demonstrated using tissue-stain-specific deep neural ***,we present a new deep-learning-based framework that generates virtually stained images using label-free tissue images,in which different stains are merged following a micro-structure map defined by the *** approach uses a single deep neural network that receives two different sources of information as its input:(1)autofluorescence images of the label-free tissue sample and(2)a“digital staining matrix”,which represents the desired microscopic map of the different stains to be virtually generated in the same tissue *** digital staining matrix is also used to virtually blend existing stains,digitally synthesizing new histological *** trained and blindly tested this virtual-staining network using unlabelled kidney tissue sections to generate micro-structured combinations of haematoxylin and eosin(H&E),Jones’silver stain,and Masson’s trichrome *** a single network,this approach multiplexes the virtual staining of label-free tissue images with multiple types of stains and paves the way for synthesizing new digital histological stains that can be created in the same tissue cross section,which is currently not feasible with standard histochemical staining methods.

关键词： network rendering synthesis

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Benchmarking a Quantum Random Number Generator with Machine Learning

Benchmarking a Quantum Random Number Generator with Machine ...

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Conference on Quantum Information and Measurement, ICQI 2021

作者： Haw, Jing Yan Truong, Nhan Duy Ng, Hong Jie Ho, Raymond Assad, Syed Wang, Chao Lam, Ping Koy Kavehei, Omid Department of Electrical & Computer Engineering National University of Singapore 117583 Singapore Centre for Quantum Computation and Communication Technology Department of Quantum Science Australian National University CanberraACT2601 Australia Australian Research Council Training Centre for Innovative BioEngineering The University of Sydney NSW2006 Australia NeuroSyd Lab School of Biomedical Engineering Faculty of Engineering The University of Sydney NSW2006 Australia

We develop a predictive machine learning (ML) analysis to examine the uniformity and unpredictability aspects of a random number generator. We show that our tool is capable of uncovering hidden correlations and experi... 详细信息

ISBN: (纸本)9781957171012

关键词： Machine learning

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Manipulating Fano coupling in an opto-thermoelectric field

arXiv

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arXiv 2024年

作者： Lin, Linhan Lepeshov, Sergey Krasnok, Alex Huang, Yu Jiang, Taizhi Peng, Xiaolei Korgel, Brian A. Alu, Andrea Zheng, Yuebing State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision Instrument Tsinghua University Beijing100084 China Department of Electrical and Photonics Engineering DTU Electro Technical University of Denmark Building 343 Kgs. LyngbyDK-2800 Denmark Department of Electrical and Computer Engineering Florida International University MiamiFL33174 United States School of Physics and Electronics Hunan University Changsha410082 China Mc Ketta Department of Chemical Engineering The University of Texas at Austin AustinTX78712 United States Materials Science & Engineering Program Texas Materials Institute The University of Texas at Austin AustinTX78712 United States Department of Electrical and Computer Engineering The University of Texas at Austin AustinTX78712 United States Advanced Science Research Center City University of New York New YorkNY10031 United States Physics Program Graduate Center City University of New York NY10016 United States Walker Department of Mechanical Engineering The University of Texas at Austin AustinTX78712 United States

Fano resonances in photonics arise from the coupling and interference between two resonant modes in structures with broken symmetry. They feature an uneven and narrow and tunable lineshape, and are ideally suited for optical spectroscopy. Many Fano resonance structures have been suggested in nanophotonics over the last ten years, but reconfigurability and tailored design remain challenging. Herein, we propose an all-optical "pick-and-place" approach aimed at assemble Fano metamolecules of various geometries and compositions in a reconfigurable manner. We study their coupling behavior by in-situ dark-field scattering spectroscopy. Driven by a light-directed opto-thermoelectric field, silicon nanoparticles with high quality-factor Mie resonances (discrete states) and low-loss BaTiO3 nanoparticles (continuum states) are assembled into all-dielectric heterodimers, where distinct Fano resonances are observed. The Fano parameter can be adjusted by changing the resonant frequency of the discrete states or the light polarization. We also show tunable coupling strength and multiple Fano resonances by altering the number of continuum states and discrete states in dielectric heterooligomers. Our work offers a general design rule for Fano resonance and an all-optical platform for controlling Fano coupling on demand. Copyright © 2024, The Authors. All rights reserved.

关键词： Light polarization

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DCGAN-based Medical Image Augmentation to Improve ELM Classification Performance

DCGAN-based Medical Image Augmentation to Improve ELM Classi...

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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Rando Noor Akhmad Setiawan Adhistya Erna Permanasari Riries Rulaningtyas Andriyan Bayu Suksmono Imas Sukaesih Sitanggang Dept. of Electrical and Information Engineering Universitas Gadjah Mada Yogyakarta Indonesia Dept. of Physics Universitas Airlangga Biomedical Engineering Program Surabaya Indonesia School of Electrical Engineering and Informatics Institut Teknologi Bandung Bandung Indonesia Department of Computer Science IPB University Bogor Indonesia

ISBN: (数字)9781665460309

ISBN: (纸本)9781665460316

Cervical cancer is one of the deadliest diseases in women. One of the cervical cancer screening methods is pap smear method. However, using a pap smear method to detect cervical cancer takes a long time for a pathologist to diagnose. Hence, a rapid development of medical computerization for early detection to get the results quickly is needed. This paper proposes synthetic data augmentation by using Deep Convolutional Generative Adversarial Network (DCGAN) to increase number of pap smear samples in dataset. Gray Level Co-occurrence Matrix (GLCM) is employed to extract features from dataset. Classification of 3 classes which are Adenocarcinoma, High-Grade Squamous Intraepithelial Lesion (HSIL), and Squamous Cell Carcinoma (SCC) is conducted using Extreme Learning Machine (ELM). The result shows that the addition of synthetic data improves the performance of ELM with the accuracy of 90%. This accuracy is better than the accuracy of ELM using only the original dataset which is 85%.

关键词： Satellites Extreme learning machines Medical services Feature extraction Generative adversarial networks Entropy Lesions

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Electrochemical measurement of serotonin by Au-CNT electrodes fabricated on microporous cell culture membranes

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Microsystems & Nanoengineering 2020年第1期6卷 494-506页

作者： Ashley A.Chapin Pradeep R.Rajasekaran David N.Quan Liangbing Hu Jens Herberholz William E.Bentley Reza Ghodssi Fischell Department of Bioengineering College ParkMD 20742USA Institute for Systems Research College ParkMD 20740USA Department of Materials Science and Engineering College ParkMD 20740USA Department of Psychology and Neuroscience and Cognitive Science Program College ParkMD 20740USA Institute for Bioscience and Biotechnology Research RockvilleMD 20850USA Robert E.Fischell Institute for Biomedical Devices RockvilleMD 20850USA Department of Electrical and Computer Engineering College ParkMD 20742USA

Gut–brain axis(GBA)communication relies on serotonin(5-HT)signaling between the gut epithelium and the peripheral nervous system,where 5-HT release patterns from the basolateral(i.e.,bottom)side of the epithelium activate nerve *** have been few quantitative studies of this gut-neuron signaling due to a lack of real-time measurement tools that can access the basolateral gut *** vitro platforms allow quantitative studies of cultured gut tissue,but they mainly employ offline and endpoint assays that cannot resolve dynamic molecular-release ***,we present the modification of a microporous cell culture membrane with carbon nanotube-coated gold(Au-CNT)electrodes capable of continuous,label-free,and direct detection of 5-HT at physiological *** characterization of single-walled carbon nanotube(SWCNT)-coated Au electrodes shows increased electroactive surface area,5-HT specificity,sensitivity,and saturation time,which are correlated with the CNT film drop-cast *** microliters of CNT films,with a 10-min saturation time,0.6μA/μM 5-HT sensitivity,and reliable detection within a linear range of 500 nM–10μM 5-HT,can be targeted for high-concentration,high-time-resolution 5-HT *** films(12.5μL)with a 2-h saturation time,4.5μA/μM 5-HT sensitivity,and quantitative detection in the linear range of 100 nM–1μM can target low concentrations with low time *** electrodes achieved continuous detection of dynamic diffusion across the porous membrane,mimicking basolateral 5-HT release from cells,and detection of cell-released 5-HT from separately cultured RIN14B cell ***-integrated cell culture systems such as this can improve in vitro molecular detection mechanisms and aid in quantitative GBA signaling studies.

关键词： release saturation dynamic

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Analog, In-memory Compute Architectures for Artificial Intelligence

arXiv

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arXiv 2023年

作者： Bowen, Patrick Regev, Guy Regev, Nir Pedroni, Bruno Umbria Hanson, Edward Chen, Yiran Neurophos 212 W Main St. #301 DurhamNC27701 United States Center for Metamaterials and Integrated Plasmonics Department of Electrical and Computer Engineering Duke University P.O. Box 90291 DurhamNC27708 United States AlephZero 5141 Beeman Ave. Valley VillageCA91607 United States Department of Electrical and Computer Engineering Ben-Gurion University of the Negev David Ben-Gurion Blvd. 1 Be'er Sheva Israel Department of Bioengineering UC San Diego 9500 Gilman Dr. La Jolla CA92093 United States Duke University Electrical and Computer Engineering Department Science Dr DurhamNC27710 United States

This paper presents an analysis of the fundamental limits on energy efficiency in both digital and analog in-memory computing architectures, and compares their performance to single instruction, single data (scalar) machines specifically in the context of machine inference. The focus of the analysis is on how efficiency scales with the size, arithmetic intensity, and bit precision of the computation to be performed. It is shown that analog, in-memory computing architectures can approach arbitrarily high energy efficiency as both the problem size and processor size scales. © 2023, CC BY-NC-SA.

关键词： Energy efficiency

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Enhancing UAV Spraying Efficiency through Payload Sensor Integration

Enhancing UAV Spraying Efficiency through Payload Sensor Int...

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IEEE Latin American Robotics Symposium, LARS

作者： Celso O. Barcelos Leonardo A. Fagundes-Júnior Daniel C. Gandolfo Martin Saska Alexandre S. Brandão Department of Electrical Engineering Graduate Program in Computer Science Núcleo de Especialização em Robótica (NERo) Universidade Federal de Viçosa Viçosa MG Brazil Instituto de Automática National University of San Juan San Juan Argentine Department of Cybernetics Czech Technical University in Prague Prague Czech Republic

ISBN: (数字)9798331508807

ISBN: (纸本)9798331508814

The use of UAVs has grown in recent years, leading to the prominence of various applications such as monitoring and inspection, search and rescue operations, dam and civil structure inspection, military applications, among others. One of the most relevant applications today is related to Precision Agriculture, which is the subject of this work. Our study analyzes the behavior of an Unmanned Autonomous Vehicle (UAV) used for spraying tasks. The variation of the payload is measured through a load sensor. This information indicates to the UAV the right time to return to the base for refueling or completion of the application. Experimental validation is carried out to assess the functionality of the payload sensor during flight operations. In addition, the dynamic compensation controller improves the navigation of the UAV, even in the presence of payload variations during the entire mission duration.

关键词： Precision agriculture Navigation Spraying Inspection Robot sensing systems Autonomous aerial vehicles Vehicle dynamics Monitoring Payloads Diseases

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Virtual impactor-based label-free bio-aerosol detection using holography and deep learning

arXiv

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arXiv 2022年

作者： Luo, Yi Zhang, Yijie Liu, Tairan Yu, Alan Wu, Yichen Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los AngelesCA90095 United States University of California Los AngelesCA90095 United States Computer Science Department University of California Los AngelesCA90095 United States

Exposure to bio-aerosols such as mold spores and pollen can lead to adverse health effects. There is a need for a portable and cost-effective device for long-term monitoring and quantification of various bio-aerosols. To address this need, we present a mobile and cost-effective label-free bio-aerosol sensor that takes holographic images of flowing particulate matter concentrated by a virtual impactor, which selectively slows down and guides particles larger than 6μm to fly through an imaging window. The flowing particles are illuminated by a pulsed laser diode, casting their inline holograms on a CMOS image sensor in a lens-free mobile imaging device. The illumination contains three short pulses with a negligible shift of the flowing particle within one pulse, and triplicate holograms of the same particle are recorded at a single frame before it exits the imaging field-of-view, revealing different perspectives of each particle. The particles within the virtual impactor are localized through a differential detection scheme, and a deep neural network classifies the aerosol type in a label-free manner, based on the acquired holographic images. We demonstrated the success of this mobile bio-aerosol detector with a virtual impactor using different types of pollen (i.e., bermuda, elm, oak, pine, sycamore, and wheat) and achieved a blind classification accuracy of 92.91%. This mobile and cost-effective device weighs ~700 g and can be used for label-free sensing and quantification of various bio-aerosols over extended periods since it is based on a cartridge-free virtual impactor that does not capture or immobilize particulate matter. Copyright © 2022, The Authors. All rights reserved.

关键词： Holograms

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