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Predicting 1-year mortality of acute kidney injury: A risk model using electronic health records

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Predicting 1-year mortality of acute kidney injury: A risk m...

International Forum on Medical Imaging in Asia 2021, IFMIA 2021

作者： Huang, Chao-Jung Wu, Brian Li, Xiaodong Han, Yongxia Zhang, Yaqi Hao, Shiying Ling, Xuefeng B. National Taiwan University-Stanford Joint Program Office of AI in Biotechnology Ministry of Science and Technology Joint Research Center for Artificial Intelligence Technology and All Vista Healthcare Taipei Taiwan Clinical Research University of California San Diego San DiegoCA92093 United States School of Computer Science and Technology Hangzhou Dianzi University Hangzhou China School of Electrical Power Engineering South China University of Technology Guangzhou China Department of Surgery Stanford University StanfordCA94305 United States Department of Cardiothoracic Surgery Stanford University StanfordCA94305 United States Clinical and Translational Research Program Betty Irene Moore Children's Heart Center Lucile Packard Children's Hospital Palo AltoCA94305 United States

ISBN: (数字)9781510644212

ISBN: (纸本)9781510644205

Acute kidney injury (AKI) is associated with increased morbidity and mortality in intensive care units (ICU). The sudden episode of kidney failure may lead to end-stage renal disease (ESRD) or deaths, and has been related to significantly increasing costs of ICU admissions and treatments. Early prediction of AKI inpatient mortality will help decision-making, and benefit resource allocation in ICU. Therefore, it is crucial to develop an early warning system for AKI prediction. We aimed to create a more comprehensive predictive model for 1-year AKI mortality. A cohort of 2,247 patients with AKI was assembled, of which the in-hospital mortality was 36.67%. Longitudinal data of each patient were collected from the Medical Information Mart for Intensive Care III (MIMIC-III) dataset. An interpretable XGBoost risk model was developed and validated by 10-fold cross validation. Model predictors included 11 routinely collected AKI-related laboratory measurements, 8 complications of AKI, and demographic data. An artificial neural network (ANN) model was also developed in parallel for comparison. The XGBoost model demonstrated an area under the receiver-operating characteristic curve (AUC) of 0.83, which was superior to ANN (AUC = 0.79). Our model was able to predict mortality of AKI in ICU with high accuracy. Our model can predict 1-year AKI mortality. Furthermore, it had great potential for identifying at-risk patients in ICU. These findings indicated that our approach might offer opportunities for better resource utilization and better administration of AKI. © 2021 SPIE.

关键词： Neural networks

CubeSat single-photon detector module for investigating in-orbit laser annealing to heal radiation damage

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arXiv 2024年

作者： Sultana, Nigar Krynski, Joanna Lim, Jin Gyu Floyd, John Lembeck, Michael Makarov, Vadim Kwiat, Paul Jennewein, Thomas Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada University of Illinois Urbana-Champaign ChampaignIL United States Vigo Quantum Communication Center University of Vigo Vigo Spain Quantum Information Science Program Canadian Institute for Advanced Research TorontoONM5G 1Z8 Canada

Single-photon avalanche photodiodes (SPADs) based on silicon are widely considered for quantum satellite communications but suffer from an increasing dark count rate (DCR) due to displacement damage in their active areas induced by proton radiation. When the DCR of SPADs exceeds a certain threshold, they become unusable for quantum communication protocols. Previous laboratory experiments have demonstrated that laser annealing of SPADs’ active area with about 1 W optical power can significantly reduce radiation-induced DCR of synthetically irradiated SPADs. To assess the feasibility of in-orbit laser annealing on constantly irradiated SPADs in low-Earth orbit, we developed a module with a CubeSat form factor capable of both laser and thermal annealing of four silicon SPADs. Here we report the design and ground testing of this module, investigating laser annealing in a simulated space environment. Our results pave the way for an in-orbit trial that may prove this technology useful for future satellite missions with quantum receivers on board. Copyright © 2024, The Authors. All rights reserved.

关键词： Radiation damage

Gene knockout inference with variational graph autoencoder learning single-cell gene regulatory networks

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Nucleic acids research 2023年第13期51卷 6578-6592页

作者： Yongjian Yang Guanxun Li Yan Zhong Qian Xu Bo-Jia Chen Yu-Te Lin Robert S Chapkin James J Cai Department of Electrical and Computer Engineering Texas A&M University College Station TX 77843 USA. Department of Statistics Texas A&M University College Station TX 77843 USA. Key Laboratory of Advanced Theory and Application in Statistics and Data Science-MOE School of Statistics East China Normal University 3663 North Zhongshan Road Shanghai 200062 China. Department of Veterinary Integrative Biosciences Texas A&M University College Station TX 77843 USA. Graduate Institute of Microbiology and Public Health College of Veterinary Medicine National Chung Hsing University Taichung 402 Taiwan. Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taipei Taiwan. Program in Integrative & Complex Diseases Department of Nutrition Texas A&M University College Station TX 77843 USA. Interdisciplinary Program of Genetics Texas A&M University College Station TX 77843 USA.

In this paper, we introduce Gene Knockout Inference (GenKI), a virtual knockout (KO) tool for gene function prediction using single-cell RNA sequencing (scRNA-seq) data in the absence of KO samples when only wild-type (WT) samples are available. Without using any information from real KO samples, GenKI is designed to capture shifting patterns in gene regulation caused by the KO perturbation in an unsupervised manner and provide a robust and scalable framework for gene function studies. To achieve this goal, GenKI adapts a variational graph autoencoder (VGAE) model to learn latent representations of genes and interactions between genes from the input WT scRNA-seq data and a derived single-cell gene regulatory network (scGRN). The virtual KO data is then generated by computationally removing all edges of the KO gene-the gene to be knocked out for functional study-from the scGRN. The differences between WT and virtual KO data are discerned by using their corresponding latent parameters derived from the trained VGAE model. Our simulations show that GenKI accurately approximates the perturbation profiles upon gene KO and outperforms the state-of-the-art under a series of evaluation conditions. Using publicly available scRNA-seq data sets, we demonstrate that GenKI recapitulates discoveries of real-animal KO experiments and accurately predicts cell type-specific functions of KO genes. Thus, GenKI provides an in-silico alternative to KO experiments that may partially replace the need for genetically modified animals or other genetically perturbed systems.

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Spectral DiffuserCam: lensless snapshot hyperspectral imaging with a spectral filter array

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arXiv 2020年

作者： Monakhova, Kristina Yanny, Kyrollos Aggarwal, Neerja Waller, Laura Department of Electrical Engineering & Computer Sciences University of California BerkeleyCA94720 United States UCB/UCSF Joint Graduate Program in Bioengineering University of California BerkeleyCA94720 United States

Hyperspectral imaging is useful for applications ranging from medical diagnostics to crop monitoring;however, traditional scanning hyperspectral imagers are prohibitively slow and expensive for widespread adoption. Snapshot techniques exist but are often confined to bulky bench-top setups or have low spatio-spectral resolution. In this paper, we propose a novel, compact, and inexpensive computational camera for snapshot hyperspectral imaging. Our system consists of a repeated spectral filter array placed directly on the image sensor and a diffuser placed close to the sensor. Each point in the world maps to a unique pseudorandom pattern on the spectral filter array, which encodes multiplexed spatio-spectral information. A sparsity-constrained inverse problem solver then recovers the hyperspectral volume with good spatio-spectral resolution. By using a spectral filter array, our hyperspectral imaging framework is flexible and can be designed with contiguous or non-contiguous spectral filters that can be chosen for a given application. We provide theory for system design, demonstrate a prototype device, and present experimental results with high spatio-spectral resolution. © 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement Copyright © 2020, The Authors. All rights reserved.

关键词： Spectroscopy

Tuning cooperative behavior in games with nonlinear opinion dynamics

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arXiv 2021年

作者： Park, Shinkyu Bizyaeva, Anastasia Kawakatsu, Mari Franci, Alessio Leonard, Naomi Ehrich Computer Electrical and Mathematical Science and Engineering Division Thuwal23955-6900 Saudi Arabia Department of Mechanical and Aerospace Engineering Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States Mathematics Department National Autonomous University of Mexico Mexico City04510 Mexico

We examine the tuning of cooperative behavior in repeated multi-agent games using an analytically tractable, continuous-time, nonlinear model of opinion dynamics. Each modeled agent updates its real-valued opinion about each available strategy in response to payoffs and other agent opinions, as observed over a network. We show how the model provides a principled and systematic means to investigate behavior of agents that select strategies using rationality and reciprocity, key features of human decision-making in social dilemmas. For two-strategy games, we use bifurcation analysis to prove conditions for the bistability of two equilibria and conditions for the first (second) equilibrium to reflect all agents favoring the first (second) strategy. We prove how model parameters, e.g., level of attention to opinions of others (reciprocity), network structure, and payoffs, influence dynamics and, notably, the size of the region of attraction to each stable equilibrium. We provide insights by examining the tuning of the bistability of mutual cooperation and mutual defection and their regions of attraction for the repeated prisoner's dilemma and the repeated multi-agent public goods game. Our results generalize to games with more strategies, heterogeneity, and additional feedback dynamics, such as those designed to elicit cooperation. Copyright © 2021, The Authors. All rights reserved.

关键词： Bifurcation (mathematics)

A PARALLEL VARIATIONAL MESH QUALITY IMPROVEMENT METHOD FOR TETRAHEDRAL MESHES 28

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A PARALLEL VARIATIONAL MESH QUALITY IMPROVEMENT METHOD FOR T...

28th International Meshing Roundtable, IMR 2019

作者： Shontz, Suzanne M. Varilla, M.A.L. Huang, Weizhang Department of Electrical Engineering and Computer Science Bioengineering Program Information and Telecommunication Technology Center University of Kansas LawrenceKS United States Husky Injection Molding Systems Ltd. Luxembourg Luxembourg Department of Mathematics University of Kansas LawrenceKS United States

ISBN: (纸本)9781733489003

There are numerous large-scale applications requiring mesh adaptivity, e.g., computational uid dynamics and weather prediction. Parallel processing is needed for simulations involving large-scale adaptive meshes. In this paper, we propose a parallel variational mesh quality improvement algorithm for use with distributed memory machines. Our method parallelizes the serial variational mesh quality improvement method by Huang and Kamenski. Their approach is based on the use of the Moving Mesh PDE method to adapt the mesh based on the minimization of an energy functional for mesh equidistribution and alignment. This leads to a system of ordinary differential equations (ODEs) to be solved which determine where to move the interior mesh nodes. An efficient solution is obtained by solving the ODEs on subregions of the mesh with overlapped communication and computation. Strong and weak scaling experiments on up to 128 cores for meshes with up to 160M elements demonstrate excellent results. © 2019 Proceedings of the 28th International Meshing Roundtable, IMR 2019. All rights reserved.

关键词： Ordinary differential equations

Non-linear optics at twist interfaces in h-BN/SiC heterostructures

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arXiv 2023年

作者： Biswas, Abhijit Xu, Rui Alvarez, Gustavo A. Zhang, Jin Christiansen-Salameh, Joyce Puthirath, Anand B. Burns, Kory Hachtel, Jordan A. Li, Tao Iyengar, Sathvik Ajay Gray, Tia Li, Chenxi Zhang, Xiang Kannan, Harikishan Elkins, Jacob Pieshkov, Tymofii S. Vajtai, Robert Birdwell, A. Glen Neupane, Mahesh R. Garratt, Elias J. Ivanov, Tony Pate, Bradford B. Zhao, Yuji Zhu, Hanyu Tian, Zhiting Rubio, Angel Ajayan, Pulickel M. Department of Materials Science and Nanoengineering Rice University HoustonTX77005 United States Sibley School of Mechanical and Aerospace Engineering Cornell University IthacaNY14853 United States Max Planck Institute for the Structure and Dynamics of Matter Center for Free-Electron Laser Science Luruper Chaussee 149 22761 Germany Department of Materials Science & Engineering University of Virginia CharlottesvilleVA22904 United States Center for Nanophase Materials Sciences Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Electrical and Computer Engineering Rice University HoustonTX77005 United States DEVCOM Army Research Laboratory RF Devices and Circuits AdelphiMD20783 United States Chemistry Division Naval Research Laboratory WashingtonDC20375 United States Applied Physics Graduate Program Smalley-Curl Institute Rice University HoustonTX77005 United States Flatiron Institute New YorkNY10010 United States

Understanding the emergent electronic structure in twisted atomically thin layers has led to the exciting field of twistronics. However, practical applications of such systems are challenging since the specific angular correlations between the layers must be precisely controlled and the layers have to be single crystalline with uniform atomic ordering. Here, we suggest an alternative, simple and scalable approach where nanocrystalline two-dimensional (2D) film on three-dimensional (3D) substrates yield twisted-interface-dependent properties. Ultrawidebandgap hexagonal boron nitride (h-BN) thin films are directly grown on high in-plane lattice mismatched wide-bandgap silicon carbide (4H-SiC) substrates to explore the twist-dependent structure-property correlations. Concurrently, nanocrystalline h-BN thin film shows strong nonlinear second-harmonic generation and ultra-low cross-plane thermal conductivity at room temperature, which are attributed to the twisted domain edges between van der Waals stacked nanocrystals with random in-plane orientations. First-principles calculations based on time-dependent density functional theory manifest strong even-order optical nonlinearity in twisted h-BN layers. Our work unveils that directly deposited 2D nanocrystalline thin film on 3D substrates could provide easily accessible twist-interfaces, therefore enabling a simple and scalable approach to utilize the 2D-twistronics integrated in 3D material devices for next-generation nanotechnology. © 2023, CC BY.

关键词： Harmonic generation

Radar Occupancy Prediction with Lidar Supervision while Preserving Long-Range Sensing and Penetrating Capabilities

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arXiv 2021年

作者： Kung, Pou-Chun Wang, Chieh-Chih Lin, Wen-Chieh The Graduate Degree Program of Robotics National Yang Ming Chiao Tung University Hsinchu Taiwan The Department of Electrical and Computer Engineering National Yang Ming Chiao Tung University Taiwan The Mechanical and Mechatronics Systems Research Laboratories Industrial Technology Research Institute Hsinchu Taiwan The Department of Computer Science National Yang Ming Chiao Tung University Hsinchu Taiwan

Radar shows great potential for autonomous driving by accomplishing long-range sensing under diverse weather conditions. But radar is also a particularly challenging sensing modality due to the radar noises. Recent works have made enormous progress in classifying free and occupied spaces in radar images by leveraging lidar label supervision. However, there are still several unsolved issues. Firstly, the sensing distance of the results is limited by the sensing range of lidar. Secondly, the performance of the results is degenerated by lidar due to the physical sensing discrepancies between the two sensors. For example, some objects visible to lidar are invisible to radar, and some objects occluded in lidar scans are visible in radar images because of the radar's penetrating capability. These sensing differences cause false positive and penetrating capability degeneration, respectively. In this paper, we propose training data preprocessing and polar sliding window inference to solve the issues. The data preprocessing aims to reduce the effect caused by radar-invisible measurements in lidar scans. The polar sliding window inference aims to solve the limited sensing range issue by applying a near-range trained network to the long-range region. Instead of using common Cartesian representation, we propose to use polar representation to reduce the shape dissimilarity between long-range and near-range data. We find that extending a near-range trained network to long-range region inference in the polar space has 4.2 times better IoU than in Cartesian space. Besides, the polar sliding window inference can preserve the radar penetrating capability by changing the viewpoint of the inference region, which makes some occluded measurements seem non-occluded for a pretrained network. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical radar

Radio-transparent dipole antenna based on a metasurface cloak

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arXiv 2021年

作者： Soric, Jason Ra'di, Younes Farfan, Diego Alù, Andrea Department of Electrical and Computer Engineering University of Texas at Austin AustinTX78712 United States Photonics Initiative Advanced Science Research Center City University of New York NY10031 United States Physics Program Graduate Center City University of New York NY10016 United States Department of Electrical Engineering City College of the City University of New York NY10031 United States

Antenna technology is at the basis of ubiquitous wireless communication systems and sensors. Radiation is typically sustained by conduction currents flowing around resonant metallic objects that are optimized to enhance efficiency and bandwidth. However, resonant conductors are prone to large scattering of impinging waves, leading to challenges in crowded antenna environments due to blockage and distortion. Metasurface cloaks have been explored in the quest of addressing this challenge by reducing antenna scattering, but with limited performance in terms of bandwidth, footprint and overall scattering reduction. Here we introduce a different route towards radio-transparent antennas, in which the cloak itself acts as the radiating element, drastically reducing the overall footprint while enhancing scattering suppression and bandwidth, without sacrificing other relevant radiation metrics compared to conventional antennas. This technique offers a new application of cloaking technology, with promising features for crowded wireless communication platforms and noninvasive sensing. © 2021, CC BY-NC-ND.

关键词： Bandwidth