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Miniscope3D:optimized single-shot miniature 3D fluorescence microscopy

Light(science & Applications) 2020年第1期9卷 367-379页

作者： Kyrollos Yanny Nick Antipa William Liberti Sam Dehaeck Kristina Monakhova Fanglin Linda Liu Konlin Shen Ren Ng Laura Waller UCB/UCSF Joint Graduate Program in Bioengineering University of CaliforniaBerkeleyCA 94720USA Department of Electrical Engineering&Computer Sciences University of CaliforniaBerkeleyCA 94720USA TIPs Department Universite libre de Bruxelles(ULB)1050 BrusselsBelgium

Miniature fluorescence microscopes are a standard tool in systems ***,widefield miniature microscopes capture only 2D information,and modifications that enable 3D capabilities increase the size and weight and have poor resolution outside a narrow depth ***,we achieve the 3D capability by replacing the tube lens of a conventional 2D Miniscope with an optimized multifocal phase mask at the objective’s aperture *** the phase mask at the aperture stop significantly reduces the size of the device,and varying the focal lengths enables a uniform resolution across a wide depth *** phase mask encodes the 3D fluorescence intensity into a single 2D measurement,and the 3D volume is recovered by solving a sparsity-constrained inverse *** provide methods for designing and fabricating the phase mask and an efficient forward model that accounts for the fieldvarying aberrations in miniature *** demonstrate a prototype that is 17mm tall and weighs 2.5 grams,achieving 2.76μm lateral,and 15μm axial resolution across most of the 900×700×390μm^(3) volume at 40 volumes per *** performance is validated experimentally on resolution targets,dynamic biological samples,and mouse brain *** with existing miniature single-shot volume-capture implementations,our system is smaller and lighter and achieves a more than 2×better lateral and axial resolution throughout a 10×larger usable depth *** microscope design provides single-shot 3D imaging for applications where a compact platform matters,such as volumetric neural imaging in freely moving animals and 3D motion studies of dynamic samples in incubators and lab-on-a-chip devices.

关键词： enable resolution narrow

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Subwavelength-engineered Antislot Photonic Crystals in a Silicon Photonics Foundry for On-chip Communications

Subwavelength-engineered Antislot Photonic Crystals in a Sil...

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2024 Conference on Lasers and Electro-Optics, CLEO 2024

作者： Arnold, Kellen P. Allen, Joshua A. Halimi, Sami I. Ryder, Landen D. Afzal, Francis O. Bian, Yusheng Aboketaf, Abdelsalam Hirokawa, Takako Dezfulian, Kevin Rakowski, Michal Augur, Rod Nummy, Karen Weiss, Sharon M. Interdisciplinary Materials Science Program Vanderbilt University 2201 West End Ave NashvilleTN37235 United States Department of Electrical and Computer Engineering Vanderbilt University 2201 West End Ave NashvilleTN37235 United States NASA Goddard Space Flight Center Code 561 GreenbeltMD20771 United States GlobalFoundries 400 Stone Break Rd. Ext. MaltaNY12020 United States

ISBN: (纸本)9781957171395

We report scalable foundry fabrication and characterization of photonic crystal nanobeam waveguides incorporating subwavelength-scale dielectric antislot unit cells. This work enables enhanced light-matter interaction and three-fold improvement in VπL when incorporated in Mach-Zehnder modulators. CLEO 2024 © Optica Publishing Group 2024 © 2024 The Author(s)

关键词： Mach-Zehnder interferometers

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Robust digital molecular design of binarized neural networks 27

Robust digital molecular design of binarized neural networks

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27th International Conference on DNA Computing and Molecular programming, DNA 2021

作者： Linder, Johannes Chen, Yuan-Jyue Wong, David Seelig, Georg Ceze, Luis Strauss, Karin University of Washington Paul G. Allen School of Computer Science and Engineering SeattleWA United States Microsoft Research RedmondWA United States University of Washington Department of Bioengineering SeattleWA United States University of Washington Department of Electrical and Computer Engineering SeattleWA United States

ISBN: (纸本)9783959772051

Molecular programming - a paradigm wherein molecules are engineered to perform computation - shows great potential for applications in nanotechnology, disease diagnostics and smart therapeutics. A key challenge is to identify systematic approaches for compiling abstract models of computation to molecules. Due to their wide applicability, one of the most useful abstractions to realize is neural networks. In prior work, real-valued weights were achieved by individually controlling the concentrations of the corresponding "weight" molecules. However, large-scale preparation of reactants with precise concentrations quickly becomes intractable. Here, we propose to bypass this fundamental problem using Binarized Neural Networks (BNNs), a model that is highly scalable in a molecular setting due to the small number of distinct weight values. We devise a noise-tolerant digital molecular circuit that compactly implements a majority voting operation on binary-valued inputs to compute the neuron output. The network is also rate-independent, meaning the speed at which individual reactions occur does not affect the computation, further increasing robustness to noise. We first demonstrate our design on the MNIST classification task by simulating the system as idealized chemical reactions. Next, we map the reactions to DNA strand displacement cascades, providing simulation results that demonstrate the practical feasibility of our approach. We perform extensive noise tolerance simulations, showing that digital molecular neurons are notably more robust to noise in the concentrations of chemical reactants compared to their analog counterparts. Finally, we provide initial experimental results of a single binarized neuron. Our work suggests a solid framework for building even more complex neural network computation. © 2021 Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing. All rights reserved.

关键词： Neural networks

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Subwavelength-engineered Antislot Photonic Crystals in a Silicon Photonics Foundry for On-chip Communications

Subwavelength-engineered Antislot Photonic Crystals in a Sil...

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CLEO: science and Innovations in CLEO 2024, CLEO: S and I 2024 - Part of Conference on Lasers and Electro-Optics

关键词： Silicon photonics

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Comparison of Coherent and Incoherent Donut Beams for Deep Tissue STED Microscopy

Comparison of Coherent and Incoherent Donut Beams for Deep T...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Thariq Shanavas Robert R. McLeod Mark E. Siemens Juliet T. Gopinath Department of Physics University of Colorado Boulder CO USA Department of Electrical Computer and Energy Engineering University of Colorado Boulder CO USA Department of Physics University of Denver Denver CO Materials Science Engineering Program University of Colorado Boulder CO USA

We numerically compare the null quality for STED microscopy generated by Laguerre-Gaussian beams with orbital angular momentum and donut beams generated by incoherent addition of orthogonal Hermite Gaussian beams when... 详细信息

ISBN: (纸本)9781957171258

关键词： Biological imaging Gaussian beams Microscopy Spatial light modulators Spiral phase Step index fibers

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MICROFLUIDIC PLATFORM FOR MULTI-FREQUENCY VISCOELASTIC PHENOTYPING OF SINGLE CELLS 25

MICROFLUIDIC PLATFORM FOR MULTI-FREQUENCY VISCOELASTIC PHENO...

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25th International Conference on Miniaturized Systems for Chemistry and Life sciences, MicroTAS 2021

作者： Lai, Andre Dong, Alan Lustig, Michael Sohn, Lydia L. UC Berkeley-UC San Francisco Graduate Program in Bioengineering University of California BerkeleyCA United States Electrical Engineering and Computer Sciences University of California BerkeleyCA United States Department of Mechanical Engineering University of California BerkeleyCA United States

ISBN: (纸本)9781733419031

Biomechanics plays an integral role in cancer development and progression. Accurately quantifying the mechanical properties of cells would enable a more comprehensive understanding of cancer, complementing conventional biochemical and genetic analyses. Here, we introduce a microfluidic platform for measuring single cell viscoelasticity at multiple frequencies in a high-throughput and label-free manner. Using the Coulter principal and a unique microfluidic channel geometry, our device records resistance pulses in order to estimate a cell's viscoelastic phenotype. We demonstrate our platform's capabilities by measuring three breast epithelial cell lines. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life sciences. All rights reserved.

关键词： Biomechanics

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Visual Control and Mapping for UAV-Based Platform Inspection

Visual Control and Mapping for UAV-Based Platform Inspection

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Leonardo A. Fagundes Carlos M. Soria Raquel F. Vassallo Alexandre S. Brandão Department of Electrical Engineering Graduate Program on Computer Science Federal University of Viçosa Viçosa MG Brazil Facultad de Ingeniería Instituto de Automática Universidad Nacional de San Juan Argentine Department of Electric Engineering Federal University of Espirito Santo Vitória ES Brazil

ISBN: (数字)9798331513283

ISBN: (纸本)9798331513290

Autonomous take-off and landing capabilities are crucial in UAV vision-based missions, ensuring adaptive navigation, especially in challenging environments where realtime identification and interaction with a variety of landing platforms are required. In this context, this paper presents a servo-visual controller that uses pattern detection and color segmentation techniques to identify take-off/landing platforms and estimate their current orientation. The proposed system was subjected to experimental validation with four platforms positioned in different orientations, heights, and positions, demonstrating its versatility in various conditions. Our study addresses the Flying Robots Trial League challenge, which emulates mapping and inspection tasks in offshore platforms.

关键词： Visualization Offshore installations Navigation Color Inspection Autonomous aerial vehicles Aircraft Drones Aerospace control

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Unbiased Parameter Estimation for Bayesian Inverse Problems

arXiv

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arXiv 2025年

作者： Chada, Neil K. Jasra, Ajay Maama, Mohamed Tempone, Raul Department of Mathematics City University of Hong Kong China School of Data Science The Chinese University of Hong Kong Shenzhen CN Shenzhen China Applied Mathematics and Computational Science Program Computer Electrical and Mathematical Sciences and Engineering Division King Abdullah University of Science and Technology Thuwal23955-6900 Saudi Arabia

In this paper we consider the estimation of unknown parameters in Bayesian inverse problems. In most cases of practical interest, there are several barriers to performing such estimation, This includes a numerical approximation of a solution of a differential equation and, even if exact solutions are available, an analytical intractability of the marginal likelihood and its associated gradient, which is used for parameter estimation. The focus of this article is to deliver unbiased estimates of the unknown parameters, that is, stochastic estimators that, in expectation, are equal to the maximizer of the marginal likelihood, and possess no numerical approximation error. Based upon the ideas of [4] we develop a new approach for unbiased parameter estimation for Bayesian inverse problems. We prove unbiasedness and establish numerically that the associated estimation procedure is faster than the current state-of-the-art methodology for this problem. We demonstrate the performance of our methodology on a range of problems which include a PDE and ODE. Copyright © 2025, The Authors. All rights reserved.

关键词： Markov processes

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Multi-Instance Task in Swarm Robotics: Sorting Groups of Robots or Objects into Clusters with Minimalist Controllers

Multi-Instance Task in Swarm Robotics: Sorting Groups of Rob...

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IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Adilson Krischanski Yuri K. Lopes Andre B. Leal Ricardo F. Martins Roberto S.U. Rosso Department of Computer Science Santa Catarina State University (UDESC) Joinville Brazil Graduate Program in Applied Computing (PPGCAP) UDESC Brazil Department of Electrical Engineering Santa Catarina State University (UDESC) Joinville Brazil

Relying only on behaviors that emerge from simple responsive controllers; swarms of robots have been shown capable of autonomously aggregate themselves or objects into clusters without any form of communication. We push these controllers to the limit, requiring robots to sort themselves or objects into different clusters. Based on a responsive controller that maps the current reading of a line-of-sight sensor to a pair of speeds for the robots' differential wheels, we demonstrate how multiple tasks instances can be accomplished by a robotic swarm. Using the dividing rectangles approach and physics simulation, a training step optimizes the parameters of the controller guided by a fitness function. We conducted a series of systematic trials in physics-based simulation and evaluate the performance in terms of dispersion and the ratio of clustered robots/objects. Across 20 trials where 30 robots cluster themselves into 3 groups, an average of 99.83% of them were correctly clustered into their group after 300 s. Across 50 trials where 15 robots cluster 30 objects into 3 groups, an average of 61.20%, 82.87%, and 97.73% of objects were correctly clustered into their group after 600 s, 900 s, and 1800 s, respectively. The object cluster behavior scales well while the aggregation does not, the latter due to the requirement of control tuning based on the number of robots.

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Morphological imaging of 3D cultured kidney mesangial cells using gradient light interference microscopy

Morphological imaging of 3D cultured kidney mesangial cells ...

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Digital Holography and Three-Dimensional Imaging, DH 2024

作者： Butola, Ankit Ghosh, Biswajoy Park, Jaena Kwon, Minsung De la Cadena, Alejandro Mukherjee, Sudipta Bhargava, Rohit Boppart, Stephen A. Agarwal, Krishna Department of Physics and Technology UiT The Arctic University of Norway Tromsø9037 Norway 405 N. Mathews Ave. UrbanaIL61801 United States Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 405 N Mathews Avenue UrbanaIL61801 United States Department of Bioengineering University of Illinois at Urbana-Champaign 1406 W Green Street UrbanaIL61801 United States Department of Chemical and Biomolecular Engineering University of Illinois Urbana-Champaign UrbanaIL United States Department of Electrical and Computer Engineering University of Illinois Urbana-Champaign UrbanaIL United States Cancer Center at Illinois University of Illinois Urbana-Champaign UrbanaIL United States Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign 306 N Wright Street UrbanaIL61801 United States Carle Illinois College of Medicine University of Illinois at Urbana-Champaign 506 S Mathews Avenue UrbanaIL61801 United States

We present a gradient light interference microscopy system to visualize 3D quantitative imaging of kidney mesangial cells. We used the system to obtain the morphology of 3D cultured kidney cells of thickness 200 µ... 详细信息

关键词： Light interference

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