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SSRN 2023年

作者： Stephens, Andrew D. Song, Yujing McClellan, Brandon L. Su, Shiuan-Haur Xu, Sonnet Chen, Kevin Castro, Maria G. Singer, Benjamin H. Kurabayashi, Katsuo Department of Mechanical Engineering University of Michigan Ann ArborMI48109 United States Department of Neurosurgery University of Michigan Medical School Ann ArborMI48109 United States Department of Cell and Developmental Biology University of Michigan Medical School Ann ArborMI48109 United States Graduate Program in Immunology University of Michigan Medical School Ann ArborMI48109 United States Department of Biomedical Engineering University of Michigan Ann ArborMI48109 United States Rogel Cancer Center University of Michigan Ann ArborMI48109 United States Department of Internal Medicine Division of Pulmonary and Critical Care Medicine University of Michigan Ann ArborMI48109 United States Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109 United States Weil Institute for Critical Care Research and Innovation University of Michigan Ann ArborMI48109 United States

The search for reliable protein biomarker candidates is critical for early disease detection and treatment. However, current immunoassay technologies are failing to meet increasing demands for sensitivity and multiplexing. Here, the authors have created a highly sensitive protein microarray using the principle of single-molecule counting for signal amplification, capable of simultaneously detecting a panel of cancer biomarkers at sub-pg/mL levels. To enable this amplification strategy, the authors introduce a novel method of protein patterning using photolithography to subdivide addressable arrays of capture antibody spots into hundreds of thousands of individual microwells. This allows for the total sensor area to be miniaturized, increasing the total possible multiplex capacity. With the immunoassay realized on a standard 75x25 mm form factor glass substrate, sample volume consumption is minimized to © 2023, The Authors. All rights reserved.

关键词： Biomarkers

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Thompson-Sampling-Based Wireless Transmission for Panoramic Video Streaming

Thompson-Sampling-Based Wireless Transmission for Panoramic ...

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International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks (WiOpt)

作者： Jiangong Chen Bin Li R. Srikant Department of Electrical Computer and Biomedical Engineering at the University of Rhode Island Kingston RI USA Department of Electrical and Computer Engineering Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign Urbana IL USA

ISBN: (数字)9783903176294

ISBN: (纸本)9781728193892

Panoramic video streaming has received great attention recently due to its immersive experience. Different from traditional video streaming, it typically consumes 4 ~ 6× larger bandwidth with the same resolution. Fortunately, users can only see a portion (roughly 20%) of 360° scenes at each time and thus it is sufficient to deliver such a portion, namely Field of View (FoV), if we can accurately predict user's motion. In practice, we usually deliver a portion larger than FoV to tolerate inaccurate prediction. Intuitively, the larger the delivered portion, the higher the prediction accuracy. This however leads to a lower transmission success probability. The goal is to select an appropriate delivered portion to maximize system throughput, which can be formulated as a multi-armed bandit problem, where each arm represents the delivered portion. Different from traditional bandit problems with single feedback information, we have two-level feedback information (i.e., both prediction and transmission outcomes) after each decision on the selected portion. As such, we propose a Thompson Sampling algorithm based on two-level feedback information, and demonstrate its superior performance than its traditional counterpart via simulations.

关键词： Prediction algorithms Streaming media Throughput Wireless communication Predictive models Bandwidth Adaptation models

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Spatially-varying microscope calibration from unstructured sparse inputs

Spatially-varying microscope calibration from unstructured s...

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Computational Optical Sensing and Imaging, COSI 2020 - Part of Imaging and Applied Optics Congress 2020

作者： Kuo, Grace Monakhova, Kristina Yanny, Kyrollos Ng, Ren Waller, Laura Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94720 United States UCB/UCSF Joint Graduate Program in Bioengineering University of California Berkeley BerkeleyCA94720 United States

We propose a method based on blind deconvolution to calibrate the spatially-varying point spread functions of a coded-aperture microscope system. From easy-to-acquire measurements of unstructured fluorescent beads, we... 详细信息

ISBN: (纸本)9781557528209

关键词： Optical transfer function

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Model Technology Service E-Participation - Voting (E-PV) for Political Communication between the Council of Regional Representatives (DPRD) and the Citizens Using the Framework Information Technology Infrastructure Library (ITIL V.3) Transition Domain Service 7

Model Technology Service E-Participation - Voting (E-PV) for...

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Hilabi, Shofa Shofiah Harso Supangat, Suhono Hendric Spits Warnars, Harco Leslie Prabowo, Harjanto Mursitama, Tirta Nugraha Universitas Buana Perjuangan Faculty of Engineering and Computer Science Karawang Indonesia Institute of Technology Bandung School of Electrical Engineering and Informatics Bandung Indonesia Nusantara University Doctor of Computer Science Bina Computer Science Department BINUS Graduate Program Jakarta11530 Indonesia Bina Nusantara University Doctor of Computer Science Jakarta11530 Indonesia Bina Nusantara University Faculty of Humanities International Relations Department Jakarta11480 Indonesia

ISBN: (纸本)9781665404228

E-voting is an electronic voting information technology service, while E-participation is an information technology service for citizens of the public to provide reports, polls, or suggestions on government policies electronically. The Technology Services E-Participation-VOT (EPV) model is a combined E-Participation and E-Voting service model. The concept of this service model is that citizens transform from E-participation and E-voting services into an EPV model. The purpose of this model is to provide information to participants (citizens) about online-based voting services. This method of developing the EP-Voting Anticipation (EPV) technology model uses agile methods that are effective and flexible in various cases of designing Information Technology models for Information Technology (IT) services that apply a Framework Information Technology Infrastructure Library (ITIL). The results obtained from this study are an Information Technology service system model that provides recommendations for participation in conducting electronic elections (E-Voting). © 2020 IEEE.

关键词： Surveys

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Implantable silicon neural probes with nanophotonic phased arrays for single-lobe beam steering

arXiv

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arXiv 2024年

作者： Chen, Fu-Der Sharma, Ankita Xue, Tianyuan Jung, Youngho Govdeli, Alperen Mak, Jason C.C. Chameh, Homeira Moradi Movahed, Mandana Brunk, Michael G.K. Luo, Xianshu Chua, Hongyao Lo, Patrick Guo-Qiang Valiante, Taufik A. Sacher, Wesley D. Poon, Joyce K.S. Max Planck Institute of Microstructure Physics Weinberg 2 Halle06120 Germany Department of Electrical and Computer Engineering University of Toronto 10 King’s College Road TorontoONM5S 3G4 Canada Max Planck-University of Toronto Centre for Neural Science and Technology Canada Krembil Brain Institute University Health Network TorontoON Canada Advanced Micro Foundry Pte. Ltd. 11 Science Park Road Singapore Science Park II 117685 Singapore Division of Neurosurgery Department of Surgery Toronto Western Hospital University of Toronto TorontoON Canada Institute of Biomedical Engineering University of Toronto TorontoON Canada

In brain activity mapping experiments using optogenetics, patterned illumination is crucial for deterministic and localized stimulation of neurons. However, due to optical scattering in brain tissue, light-emitting implantable devices are needed to bring precise patterned illumination to deep brain regions. A promising solution is silicon neural probes with integrated nanophotonic circuits that form tailored beam emission patterns without lenses. Here, we demonstrate neural probes with grating-based light emitters that generate a single steerable light beam across > 60% of the steering range with ≥ 4 dB of background suppression for optogenetic photostimulation. The light emitters, optimized for blue or amber light, combine end-fire optical phased arrays with slab gratings to suppress higher-order sidelobes. In vivo optogenetic photostimulation was demonstrated in Thy1-ChR2-YFP mice. These neural probes, capable of continuous single beam scanning, offer a promising avenue for optogenetic stimulation with cellular-level spatial precision in the deep brain. © 2024, CC BY-NC-ND.

关键词： Nanophotonics

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An Interactive Control Approach to 3D Shape Reconstruction

An Interactive Control Approach to 3D Shape Reconstruction

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American Control Conference

作者： Bipul Islam Ji Liu Anthony Yezzi Romeil Sandhu Department of Computer Science & Biomedical Informatics Stony Brook University Stony Brook NY Department of Electrical and Computer Engineering Stony Brook University Stony Brook NY Department of Electrical and Computer Engineering Georgia Tech Atlanta GA

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

The ability to accurately reconstruct the 3D facets of a scene is one of the key problems in robotic vision. However, even with recent advances with machine learning, there is no high-fidelity universal 3D reconstruction method for this optimization problem as schemes often cater to specific image modalities and are often biased by scene abnormalities. Simply put, there always remains an "information" gap due to the dynamic nature of real-world scenarios. To this end, we demonstrate a feedback control framework which invokes operator inputs (also prone to errors) in order to augment existing reconstruction schemes. For proof-of-concept, we choose a classical region-based stereoscopic reconstruction approach and show how an ill-posed model can be augmented with operator input to be much more robust to scene artifacts. We provide necessary conditions for stability via Lyapunov analysis and perhaps more importantly, we show that the stability depends on a notion of absolute curvature. Mathematically, this aligns with previous work that has shown Ricci curvature as proxy for functional robustness of dynamical networked systems. We conclude with results that show how our method can improve standalone reconstruction schemes.

关键词： Three-dimensional displays Image reconstruction Two dimensional displays Surface reconstruction Image segmentation Shape Cameras

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Dielectric spectroscopy of liver mixture model for millimetre-wave imaging

Dielectric spectroscopy of liver mixture model for millimetr...

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2019 European Microwave Conference in Central Europe, EuMCE 2019

作者： Farhat, Iman Bonello, Julian Farrugia, Lourdes Di Meo, Simona Pollacco, Daphne-Anne Sammut, Charles Department of Physics University of Malta Malta Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy

ISBN: (纸本)9782874870675

In this paper, we present a technique to mimic the dielectric properties for liver at 0.2-50 GHz based on the effective medium theory. A mathematical model based on Bruggeman mixture equation is presented to describe the dielectric properties of liver. The dielectric response of the mixture system considers two dielectric media, referred to as the host and inclusion media. In fact, proposed mixture solution consists of concentrations of Bovine Serum Albumin (BSA) in PBS solution, synthesized to mimic in-vivo liver tissue using physiological saline solutions coupled with protein additions. Generally, when testing an electromagnetic medical device in prototype phase, such solutions are required to assess the feasibility of the technology. The dielectric properties as measured experimentally are correlated to the calculated effective permittivity using Bruggemann equation. Results were then analysed, implying that such solutions can be utilised in the construction of human body phantoms for narrowband and ultra-wideband microwave devices for both millimeter-wave imaging and applications in hyperthermia and other ablation modalities. The frequency range studied could also lead to realistic phantoms for dosimetry studies related to human safety concerns. Hence, a stratified liver mixture model has been proposed which can be used as a theoretical basis for taking further steps in liver cancer research. © 2019 EuMCE.

关键词： Phantoms

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Self-organization of mouse embryonic stem cells into reproducible pre-gastrulation embryo models via CRISPRa programming

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Cell Stem Cell 2025年第6期32卷 895-913.e8页

作者： Lodewijk, Gerrald A. Kozuki, Sayaka Han, Clara J. Topacio, Benjamin R. Lee, Seungho Nixon, Lily Zargari, Abolfazl Knight, Gavin Ashton, Randolph Qi, Lei S. Shariati, S. Ali Department of Biomolecular Engineering University of California Santa Cruz Santa Cruz CA United States Genomics Institute University of California Santa Cruz Santa Cruz CA United States Institute for The Biology of Stem Cells University of California Santa Cruz Santa Cruz CA United States Department of Electrical and Computer Engineering University of California Santa Cruz Santa Cruz CA United States Neurosetta LLC Madison WI United States Wisconsin Institute for Discovery Madison WI United States Department of Biomedical Engineering University of Wisconsin-Madison Madison WI United States Department of Bioengineering Stanford University Stanford CA United States Sarafan ChEM-H Stanford University Stanford CA United States Chan Zuckerberg Biohub San Francisco San Francisco CA United States

Embryonic stem cells (ESCs) can self-organize into structures with spatial and molecular similarities to natural embryos. During development, embryonic and extraembryonic cells differentiate through activation of endogenous regulatory elements while co-developing via cell-cell interactions. However, engineering regulatory elements to self-organize ESCs into embryo models remains underexplored. Here, we demonstrate that CRISPR activation (CRISPRa) of two regulatory elements near Gata6 and Cdx2 generates embryonic patterns resembling pre-gastrulation mouse embryos. Live single-cell imaging revealed that self-patterning occurs through orchestrated collective movement driven by cell-intrinsic fate induction. In 3D, CRISPRa-programmed embryo models (CPEMs) exhibit morphological and transcriptomic similarity to pre-gastrulation mouse embryos. CPEMs allow versatile perturbations, including dual Cdx2-Elf5 activation to enhance trophoblast differentiation and lineage-specific activation of laminin and matrix metalloproteinases, uncovering their roles in basement membrane remodeling and embryo model morphology. Our findings demonstrate that minimal intrinsic epigenome editing can self-organize ESCs into programmable pre-gastrulation embryo models with robust lineage-specific perturbation capabilities. © 2025 The Author(s)

关键词： Collective Motion CRISPRa embryo models embryonic patterning epigenome editing synthetic biology

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Faster convergence in deep-predictive-coding networks to learn deeper representations

arXiv

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arXiv 2021年

作者： Sledge, Isaac J. Príncipe, José C. The Advanced Signal Processing and Automated Target Recognition Branch Naval Surface Warfare Center Panama CityFL United States The Department of Electrical and Computer Engineering University of Florida GainesvilleFL United States The Department of Biomedical Engineering University of Florida GainesvilleFL United States

Deep-predictive-coding networks (DPCNs) are hierarchical, generative models. They rely on feed-forward and feed-back connections to modulate latent feature representations of stimuli in a dynamic and context-sensitive manner. A crucial element of DPCNs is a forward-backward inference procedure to uncover sparse, invariant features. However, this inference is a major computational bottleneck. It severely limits the network depth due to learning stagnation. Here, we prove why this bottleneck occurs. We then propose a new forward-inference strategy based on accelerated proximal gradients. This strategy has faster theoretical convergence guarantees than the one used for DPCNs. It overcomes learning stagnation. We also demonstrate that it permits constructing deep and wide predictive-coding networks. Such convolutional networks implement receptive fields that capture well the entire classes of objects on which the networks are trained. This improves the feature representations compared with our lab's previous non-convolutional and convolutional DPCNs. It yields unsupervised object recognition that surpass convolutional autoencoders and are on par with convolutional networks trained in a supervised manner. © 2021, CC BY.

关键词： Convolution

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Hyperparameter Selection for Bayesian Image Reconstruction by Mimicking Physical Crystallization

Hyperparameter Selection for Bayesian Image Reconstruction b...

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2020 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2020

作者： Gao, Yongfeng Liang, Zhengrong Lu, Siming Shi, Yongyi Chang, Shaojie Hou, Wei The Department of Radiology Stony Brook University Stony Brook NY11794 United States The Department of Radiology Biomedical Engineering Computer Science and Electrical Engineering Stony Brook University Stony Brook NY11794 United States The Department of Family Population and Preventive Medicine Stony Brook University Stony Brook NY11794 United States

ISBN: (纸本)9781728176932

Although Bayesian theory has been successfully applied for count-limited medical image reconstruction in the past two decades, its wide applications in clinic has been hampered by its hyperparameter β, which is traditionally determined by a trial-error style. To eliminate the cumbersome style, this work aims to present a selection method by mimicking the physical model of cooling down the temperature adaptively for an economic high-quality crystal. From the basic Bayes' law, the physical meaning of hyperparameter can be interpreted as the ratio of the data uncertainty (or variance α) and the prior tolerance (or σ) by formulating the probability distribution functions (FDFs) of the data fidelity and prior expectation. Inspired by this idea, the prior tolerance σ can be treated as the temperature of the texture patterns, and β can be adjusted according to different texture pattern status by satisfying the condition of each PDF in the Bayes' Law during the iteration. In Simulated phantom study, realistic Poisson noise added to the pre-log transmission data model was used. Both phantom simulation and clinical patient data results show that the proposed method can provide comparable reconstructed image quality comparing to the conventional methods but with much less reconstruction time. It is observed that the parameter introduced to satisfy the prior's PDF is more sensitive to stop the iteration process. © 2020 IEEE

关键词： Phantoms

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