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arXiv 2023年

作者： Deo, Yash Dou, Haoran Ravikumar, Nishant Frangi, Alejandro F. Lassila, Toni School of Computing and School of Medicine University of Leeds Leeds United Kingdom Leeds United Kingdom Alan Turing Institute London United Kingdom Electrical Engineering and Cardiovascular Sciences Departments Ku Leuven Leuven Belgium Division of Informatics Imaging and Data Science Schools of Computer Science and Health Sciences University of Manchester Manchester United Kingdom

The Circle of Willis (CoW) is the part of cerebral vasculature responsible for delivering blood to the brain. Understanding the diverse anatomical variations and configurations of the CoW is paramount to advance research on cerebrovascular diseases and refine clinical interventions. However, comprehensive investigation of less prevalent CoW variations remains challenging because of the dominance of a few commonly occurring configurations. We propose a novel generative approach utilising a conditional latent diffusion model with shape and anatomical guidance to generate realistic 3D CoW segmentations, including different phenotypical variations. Our conditional latent diffusion model incorporates shape guidance to better preserve vessel continuity and demonstrates superior performance when compared to alternative generative models, including conditional variants of 3D GAN and 3D VAE. We observed that our model generated CoW variants that are more realistic and demonstrate higher visual fidelity than competing approaches with an FID score 53% better than the best-performing GAN-based model. © 2023, CC BY.

关键词： Diffusion

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Why Room Temperature GeSn Lasers Need Carbon

Why Room Temperature GeSn Lasers Need Carbon

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IEEE International Conference on Group IV Photonics

作者： Tuhin Dey Augustus W. Arbogast Qian Meng Shamim Reza Aaron Muhowski Joshua Cooper Rachel S. Goldman Thales Borrely Seth R. Bank Mark A. Wistey Materials Science Engineering and Commercialization Program Texas State University San Marcos Texas USA Department of Physics Texas State University San Marcos Texas USA Department of Electrical and Computer Engineering University of Texas at Austin Austin Texas USA Department of Materials Science and Engineering University of Michigan Ann Arbor MI USA Departments of MSE Physics and EECS University of Michigan Ann Arbor MI USA Department of Physics and MSEC Program Texas State University San Marcos Texas USA

Device models show GeSn lasers are limited by weak electron and photon confinement. Adding carbon offers strong conduction band offsets, freeing SiGeSn layers for separate confinement heterostructures, reducing thresh...

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A Dual-Function Uhv-Compatible Chamber for i) Low-Temperature Plasma-Assisted Oxidation, and ii) High-Temperature Rapid Thermal Processing of Si-Based Dielectric Gate Heterostructures

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MRS Online Proceedings Library 2020年第1期303卷 339-344页

作者： S. Hattangady X-L Xu M.J. Watkins B. Hornung V. Misra G. Lucovsky J.J. Wortman Departments of Materials Science and Engineering Electrical and Computer Engineering and Physics North Carolina State University Raleigh USA

A combination of i) low-temperature, 300–400°C, plasma-assisted oxidation to form the SiO2/Si interfaces, and ii) 800°C rapid thermal chemical vapor deposition, RTCVD, to deposit SiO2 thin films have been used to fabricate gate-oxide heterostructures. This sequence separates SiO2/Si interface formation by the oxidation process from the deposition of the bulk oxide layer by RTCVD. These two processes were performed in situ and sequentially in a single-chamber, ultraclean quartz reactor system. We have studied the chemistry of the interface formation process by Auger electron spectroscopy, AES, and the electrical properties of MOS devices with Al electrodes by C-V techniques.

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Synthetic Aperture Radar Image Change Detection via Layer Attention-Based Noise-Tolerant Network

arXiv

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arXiv 2022年

作者： Meng, Desen Gao, Feng Dong, Junyu Du, Qian Li, Heng-Chao School of Information Science and Engineering Ocean University of China Qingdao266100 China Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States Sichuan Provincial Key Laboratory of Information Coding and Transmission Southwest Jiaotong University Chengdu610031 China

Recently, change detection methods for synthetic aperture radar (SAR) images based on convolutional neural networks (CNN) have gained increasing research attention. However, existing CNN-based methods neglect the interactions among multilayer convolutions, and errors involved in the preclassification restrict the network optimization. To this end, we proposed a layer attention-based noise-tolerant network, termed LANTNet. In particular, we design a layer attention module that adaptively weights the feature of different convolution layers. In addition, we design a noise-tolerant loss function that effectively suppresses the impact of noisy labels. Therefore, the model is insensitive to noisy labels in the preclassification results. The experimental results on three SAR datasets show that the proposed LANTNet performs better compared to several state-of-the-art methods. The source codes are available at https://***/summitgao/LANTNet. © 2022, CC BY.

关键词： Synthetic aperture radar

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An Investigation Towards the Application of Dielectric Spectroscopy to Monitor the Impact of Diethyl Phthalate Microplastics on Marine Algae

SSRN

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SSRN 2022年

作者： Wenchao, Wu Zhang, Dayong Sophocleous, Marios Qu, Yihe Jing, Wang Chalermwisutkul, Suramate Russel, Mohammad School of Ocean Science and Technology Dalian University of Technology Liaoning Panjin124221 China Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus The Sirindhorn International Thai German Graduate School of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand

Microplastic pollutants are currently a threat to marine microorganisms, which is difficult to determine. This paper presents the development of a dielectric spectroscopy based method using a customized PCB transmission line probe for examining the electrophysiological effect of diethyl phthalate (DEP) microplastics (0-50 mg) on marine algae (***) up to 6 days of exposure. In order to amplify the electrophysiological effects, glutaraldehyde crosslinking agent was used and encapsulated on the surface of PCB probe. The reflection coefficient (S11) and the complex permittivity (ɛʹ & ɛʺ) of the Medium Under Test (MUT) was investigated in the 30 kHz–800 MHz frequency range. No of algae cell, S11, ɛʹ & ɛʺ of *** was studied against different concentration of DEP exposures for 0-6 days and a linear relationship between S11 and the days of culture when no DEP was added. At 740 MHz a slope of -0.73 dB/day and an R2 of 0.9958 was identified. Once DEP was added, the No. of algae cell stopped increasing with time and the S11 and ɛʹ & ɛʺ values followed the same trend. This dielectric spectroscopy method could be a potential real time low-cost tool to examine microplastic pollutants impacts on marine microorganisms. © 2022, The Authors. All rights reserved.

关键词： Reflection

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Optimizing Stabilizer Parities for Improved Logical Qubit Memories

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Physical Review Letters 2021年第24期127卷 240501-240501页

作者： Dripto M. Debroy Laird Egan Crystal Noel Andrew Risinger Daiwei Zhu Debopriyo Biswas Marko Cetina Chris Monroe Kenneth R. Brown Department of Physics Duke University Durham North Carolina 27708 USA Joint Quantum Institute Center for Quantum Information and Computer Science and Departments of Physics and Electrical and Computer Engineering University of Maryland College Park Maryland 20742 USA Department of Electrical and Computer Engineering Duke University Durham North Carolina 27708 USA IonQ College Park Maryland 20740 USA

We study variants of Shor’s code that are adept at handling single-axis correlated idling errors, which are commonly observed in many quantum systems. By using the repetition code structure of the Shor’s code basis states, we calculate the logical channel applied to the encoded information when subjected to coherent and correlated single qubit idling errors, followed by stabilizer measurement. Changing the signs of the stabilizer generators allows us to change how the coherent errors interfere, leading to a quantum error-correcting code which performs as well as a classical repetition code of equivalent distance against these errors. We demonstrate a factor of 3.78±1.20 improvement of the logical T2* in a distance-3 logical qubit implemented on a trapped-ion quantum computer. Even-distance versions of our Shor-code variants are decoherence-free subspaces and fully robust to identical and independent coherent idling noise.

关键词： Quantum error correction Quantum information with trapped ions Quantum memories Trapped ions

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Invited: Drug Discovery Approaches Using Quantum Machine Learning 21

Invited: Drug Discovery Approaches Using Quantum Machine Lea...

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Proceedings of the 58th Annual ACM/IEEE Design Automation Conference

作者： Junde Li Mahabubul Alam Congzhou M Sha Jian Wang Nikolay V. Dokholyan Swaroop Ghosh Department of Computer Science and Engineering Penn State University University Park Department of Electrical Engineering Penn State University University Park Department of Engineering Science and Mechanics Penn State University University Park and Department of Pharmacology Penn State College of Medicine Hershey Department of Pharmacology Penn State College of Medicine Hershey Department of Pharmacology Penn State College of Medicine Hershey and Department of Biochemistry & Molecular Biology Penn State College of Medicine Hershey and Departments of Chemistry and Biomedical Engineering Penn State University University Park Department of Computer Science and Engineering Penn State University University Park and Department of Electrical Engineering Penn State University University Park

ISBN: (纸本)9781665432740

Traditional drug discovery pipelines can require multiple years and billions of dollars of investment. Deep generative and discriminative models are widely adopted to assist in drug development. Classical machines cannot efficiently reproduce the atypical patterns of quantum computers, which may improve the quality of learned tasks. We propose a suite of quantum machine learning techniques: incorporating generative adversarial networks (GAN), convolutional neural networks (CNN) and variational auto-encoders (VAE) to generate small drug molecules, classify binding pockets in proteins, and generate large drug molecules, respectively.

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Dynamic hidden-variable network models

arXiv

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arXiv 2021年

作者： Hartle, Harrison Papadopoulos, Fragkiskos Krioukov, Dmitri Network Science Institute Northeastern University BostonMA United States Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology Limassol3036 Cyprus Northeastern University Departments of Physics Mathematics and Electrical&Computer Engineering BostonMA United States

Models of complex networks often incorporate node-intrinsic properties abstracted as hidden variables. The probability of connections in the network is then a function of these variables. Real-world networks evolve over time, and many exhibit dynamics of node characteristics as well as of linking structure. Here we introduce and study natural temporal extensions of static hidden-variable network models with stochastic dynamics of hidden variables and links. The rates of the hidden variable dynamics and link dynamics are controlled by two parameters, and snapshots of networks in the dynamic models may or may not be equivalent to a static model, depending on the location in the parameter phase diagram. We quantify deviations from static-like behavior, and examine the level of structural persistence in the considered models. We explore temporal versions of popular static models with community structure, latent geometry, and degree-heterogeneity. We do not attempt to directly model real networks, but comment on interesting qualitative resemblances, discussing possible extensions, generalizations, and applications. Copyright © 2021, The Authors. All rights reserved.

关键词： Complex networks

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Remote sensing image translation via style-based recalibration module and improved style discriminator

arXiv

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arXiv 2021年

作者： Zhang, Tiange Gao, Feng Dong, Junyu Du, Qian School of Information Science and Engineering Ocean University of China Qingdao266100 China Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States

Existing remote sensing change detection methods are heavily affected by seasonal variation. Since vegetation colors are different between winter and summer, such variations are inclined to be falsely detected as changes. In this letter, we proposed an image translation method to solve the problem. A style-based recalibration module is introduced to capture seasonal features effectively. Then, a new style discriminator is designed to improve the translation performance. The discriminator can not only produce a decision for the fake or real sample, but also return a style vector according to the channel-wise correlations. Extensive experiments are conducted on season-varying dataset. The experimental results show that the proposed method can effectively perform image translation, thereby consistently improving the season-varying image change detection performance. Our codes and data are available at https://***/summitgao/RSIT_SRM_ISD © 2021, CC BY.

关键词： Remote sensing

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An Opportunistic Network Routing Protocol for Maritime Voluntary Observation Ships

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Procedia computer science 2022年 202卷 390-393页

作者： Meiqi Ji Xuerong Cui Juan Li Hao Zhang Shibao Li Jianhang Liu College of Oceanography and Space Informatics China University of Petroleum(East China) Qingdao 266580 China College of Computer Science and Technology China University of Petroleum(East China) Qingdao 266580 China Department of Electrical Engineering Ocean University of China Qingdao 266100 China

In order to solve the issue of data transmission for maritime voluntary observation ships, an opportunistic network routing protocol (MVOS-RP) is proposed for the complicated maritime environment. The proposed protocol transmits data through the encounter between ships. A connected graph is constructed with the sending node as the vertex, and then the selection of the relay node is divided into three scenes by traversing the graph through the Breadth First Search (BFS) algorithm. We also use the ship’s Automatic identification System (AIS) information, such as the estimated time of arrival and the route of ships, to select the appropriate relay node. MVOS-RP protocol solves the transmission issue of opportunistic network in the environment of sparse nodes and poor communication link quality. Simulation is performed on Opportunistic Network Environment (ONE) platform. The results show that, compared with other protocols, the proposed protocol has a better balance in terms of data delivery rate, average latency and routing overhead. It is a reliable and efficient opportunistic network routing protocol.

关键词： Opportunistic network Routing protocol AIS

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