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The effect of Alzheimer's disease genetic factors on limbic white matter microstructure

Alzheimer's and Dementia 2025年第4期21卷 e70130页

作者： Lorenz, Anna Sathe, Aditi Zaras, Dimitrios Yang, Yisu Durant, Alaina Kim, Michael E. Gao, Chenyu Newlin, Nancy R. Ramadass, Karthik Kanakaraj, Praitayini Khairi, Nazirah Mohd Li, Zhiyuan Yao, Tianyuan Huo, Yuankai Dumitrescu, Logan Shashikumar, Niranjana Pechman, Kimberly R. Jackson, Trevor Bryan Workmeister, Abigail W. Risacher, Shannon L. Beason-Held, Lori L. An, Yang Arfanakis, Konstantinos Erus, Guray Davatzikos, Christos Habes, Mohamad Wang, Di Tosun, Duygu Toga, Arthur W. Thompson, Paul M. Mormino, Elizabeth C. Zhang, Panpan Schilling, Kurt Albert, Marilyn Kukull, Walter Biber, Sarah A. Landman, Bennett A. Johnson, Sterling C. Bendlin, Barbara Schneider, Julie Barnes, Lisa L. Bennett, David A. Jefferson, Angela L. Resnick, Susan M. Saykin, Andrew J. Hohman, Timothy J. Archer, Derek B. Vanderbilt Memory and Alzheimer's Center Vanderbilt University School of Medicine Nashville TN United States Vanderbilt Brain Institute Vanderbilt University Medical Center Nashville TN United States Department of Computer Science Vanderbilt University Nashville TN United States Department of Electrical and Computer Engineering Vanderbilt University Nashville TN United States Department of Neurology Vanderbilt University Medical Center Nashville TN United States Vanderbilt Genetics Institute Vanderbilt University Medical Center Nashville TN United States Department of Radiology and Imaging Sciences Indiana University School of Medicine Indianapolis IN United States Indiana Alzheimer's Disease Research Center Indiana University School of Medicine Indianapolis IN United States Laboratory for Behavioral Neuroscience National Institute on Aging National Institutes of Health Baltimore MD United States Department of Biomedical Engineering Illinois Institute of Technology Chicago IL United States Rush Alzheimer's Disease Center Rush University Medical Center Chicago IL United States Department of Diagnostic Radiology Rush University Medical Center Chicago IL United States Department of Radiology University of Pennsylvania Philadelphia PA United States Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases University of Texas Health Science Center at San Antonio San Antonio TX United States University of Texas Health Science Center at San Antonio San Antonio TX United States Department of Radiology and Biomedical Imaging University of California San Francisco San Francisco CA United States Laboratory of Neuroimaging USC Stevens Institute of Neuroimaging and Informatics Keck School of Medicine University of Southern California Los Angeles CA United States Imaging Genetics Center Mark and Mary Stevens Institute for Neuroimaging and Informatics Keck School of Medicine University of Southern California Marina del Rey CA United States De

INTRODUCTION: White matter (WM) microstructure is essential for brain function but deteriorates with age and in neurodegenerative conditions such as Alzheimer's disease (AD). Diffusion MRI, enhanced by advanced bi-tensor models accounting for free water (FW), enables in vivo quantification of WM microstructural differences. METHODS: To evaluate how AD genetic risk factors affect limbic WM microstructure – crucial for memory and early impacted in disease – we conducted linear regression analyses in a cohort of 2,614 non-Hispanic White aging adults (aged 50.12 to 100.85 years). The study evaluated 36 AD risk variants across 26 genes, the association between AD polygenic scores (PGSs) and WM metrics, and interactions with cognitive status. RESULTS: AD PGSs, variants in TMEM106B, PTK2B, WNT3, and apolipoprotein E (APOE), and interactions involving MS4A6A were significantly linked to WM microstructure. DISCUSSION: These findings implicate AD-related genetic factors related to neurodevelopment (WNT3), lipid metabolism (APOE), and inflammation (TMEM106B, PTK2B, MS4A6A) that contribute to alternations in WM microstructure in older adults. Highlights: AD risk variants in TMEM106B, PTK2B, WNT3, and APOE genes showed distinct associations with limbic FW-corrected WM microstructure metrics. Interaction effects were observed between MS4A6A variants and cognitive status. PGS for AD was associated with higher FW content in the limbic system. © 2025 The Author(s). Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.

关键词： Alzheimer's disease diffusion MRI free water genetic risk variants polygenic risk white matter microstructure

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Observing engineering student teams from the organization behavior perspective using linguistic analysis of student reflections and focus group interviews

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Advances in engineering Education 2015年第3期4卷

作者： Kearney, Kerri S. Damron, Rebecca Sohoni, Sohum Oklahoma State University Stillwater OK United States Oklahoma State University Writing Center Oklahoma State University Stillwater OK United States School of Electrical and Computer Engineering Oklahoma State University Stillwater OK United States School of Computing Informatics and Decision Systems Engineering Arizona State University TempeAZ United States

This paper investigates group/team development in computer engineering courses at a University in the Central USA from the perspective of organization behavior theory, specifically Tuckman's model of the stages of group development. The investigation, conducted through linguistic analysis of student reflection essays, and through focus group interviews, also presents STEM education researchers with a method to obtain nuanced information about interpersonal skills issues such as how groups and teams function. A third contribution of the paper is a review of the organizational behavior literature on teams and groups with a concern for its application to modern engineering education.

关键词： Students

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P1AC: Revisiting Absolute Pose From a Single Affine Correspondence

arXiv

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arXiv 2020年

作者： Ventura, Jonathan Kukelova, Zuzana Sattler, Torsten Baráth, Dániel Department of Computer Science & Software Engineering Cal Poly San Luis Obispo United States Visual Recognition Group Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Czech Republic Computer Vision and Geometry Group ETH Zürich Switzerland

Affine correspondences have traditionally been used to improve feature matching over wide baselines. While recent work has successfully used affine correspondences to solve various relative camera pose estimation problems, less attention has been given to their use in absolute pose estimation. We introduce the first general solution to the problem of estimating the pose of a calibrated camera given a single observation of an oriented point and an affine correspondence. The advantage of our approach (P1AC) is that it requires only a single correspondence, in comparison to the traditional point-based approach (P3P), significantly reducing the combinatorics in robust estimation. P1AC provides a general solution that removes restrictive assumptions made in prior work and is applicable to large-scale image-based localization. We propose a minimal solution to the P1AC problem and evaluate our novel solver on synthetic data, showing its numerical stability and performance under various types of noise. On standard image-based localization benchmarks we show that P1AC achieves more accurate results than the widely used P3P algorithm. Code for our method is available at https://***/jonathanventura/P1AC/. © 2020, CC BY.

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Development and preliminary evaluation of a robotic device for mri-guided needle breast biopsy

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Journal of Medical Robotics Research 2024年第3-4期9卷

作者： Ioannides, Cleanthis Antoniou, Anastasia Zinonos, Vasiliki Damianou, Christakis Department of Interventional Radiology German Oncology Center 1 Nikis Avenue 4108 Agios Athanasios Limassol Cyprus Department of Electrical Engineering Computer Engineering and Informatics Cyprus University of Technology 30 Archbishop Kyprianou Street Limassol 3036 Cyprus

This study concerns the development and evaluation of a simple and ergonomic robotic system for Magnetic Resonance Imaging (MRI)-guided needle breast biopsy with lateral needle approach. The device comprises two piezoelectrically actuated linear motion stages intended to align a needle supporter with the target for manual needle insertion. The device demonstrated submillimeter accuracy and safe operation within a 3 T clinical MRI scanner. In phantom studies, tumor simulators of varying sizes were successfully targeted in both laboratory and MRI settings. © 2024 World Scientific Publishing Company.

关键词： accuracy agar phantom breast biopsy MRI-guided positioning device

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Simres-TV: Noise and residual similarity for parameter estimation in total variation 4

Simres-TV: Noise and residual similarity for parameter estim...

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4th International Workshop on Photogrammetric and computer Vision Techniques for Video Surveillance, Biometrics and Biomedicine, PSBB 2021

作者： Prasath, V.B. Surya Hien, Nguyen Ngoc Thanh, Dang N.H. Dvoenko, Sergey Division of Biomedical Informatics Cincinnati Children's Hospital Medical Center CincinnatiOH45229 United States Department of Pediatrics University of Cincinnati College of Medicine CincinnatiOH45257 United States Department of Biomedical Informatics College of Medicine University of Cincinnati OH45267 United States Department of Electrical Engineering and Computer Science University of Cincinnati OH45221 United States Dong Thap University Cao Lanh City Viet Nam Department of Information Technology School of Business Information Technology University of Economics Ho Chi Minh City Viet Nam Institute of Applied Mathematics and Computer Science Tula State University Russia

Image restoration with regularization models is very popular in the image processing literature. Total variation (TV) is one of the important edge preserving regularization models used, however, to obtain optimal restoration results the regularization parameter needs to be set appropriately. We propose here a new parameter estimation approach for total variation based image restoration. By utilizing known noise levels we compute the regularization parameter by reducing the similarity between residual and noise variances. We use the split Bregman algorithm for the total variation along with this automatic parameter estimation step to obtain a very fast restoration scheme. Experimental results indicate the proposed parameter estimation obtained better denoised images and videos in terms of PSNR and SSIM measures and the computational overload is less compared with other approaches. © Authors 2021. CC BY 4.0 License.

关键词： Image reconstruction

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Big Data Governance for Building A Smart Cities

Big Data Governance for Building A Smart Cities

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International Conference on ICT For Smart Society (ICISS)

作者： Novan Zulkarnain Raymond Kosala Benny Ranti Suhono Harso Supangkat Computer Science Department BINUS Graduate Program Doctor of Computer Science Information Systems Department Bina Nusantara University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia Computer Science Department Universitas Indonesia Depok Indonesia School of Electrical and Informatics Engineering Institute of Technology Bandung Bandung Indonesia

There have been many studies conducted related to Smart City, IT Governance and Big Data. In this study aims to find out how the relationship between the three and how to form a framework to explain it. The methodology used is qualitative by looking for some literature on smart city framework, IT Governance framework, and a Big Data framework. From these results, an overall picture of the relationship between the three is concluded, where Big Data has a role in IT Governance. and also the relationship of IT Governance to the realization of Smart City. And the final results of this study produce a framework to explain the relationship between Smart City, IT Governance and Big Data.

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A Conceptual Persistent Healthcare Quality Improvement Process for Software Development Management

A Conceptual Persistent Healthcare Quality Improvement Proce...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBC)

作者： Jen-Chiun Lin Mei-Ju Su Po-Hsun Cheng Yung-Chien. Weng Sao-Jie Chen Jin-Shin Lai Feipei Lai Department of Electrical Engineering National Taiwan University Taipei Taiwan Graduate Institute of Electronic Engineering and Department of Electrical Engineering National Taiwan University Taipei Taiwan National Taiwan University Hospital National Taiwan University College of Medicine Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Physical Medicine and Rehabilitation and Department of Medical Informatics National Taiwan University Hospital National Taiwan University College of Medicine Taiwan

This paper illustrates a sustained conceptual service quality improvement process for the management of software development within a healthcare enterprise. Our proposed process is revised from Niland's healthcare quality information system (HQIS). This process includes functions to survey the satisfaction of system functions, describe the operation bylaws on-line, and provide on-demand training. To achieve these goals, we integrate five information systems in National Taiwan University Hospital, including healthcare information systems, health quality information system, requirement management system, executive information system, and digital learning system, to form a full Deming cycle. A preliminary user satisfaction survey showed that our outpatient information system scored an average of 71.31 in 2006.

关键词： Medical services Software development management Management information systems Quality management Programming Bylaws Management training Hospitals Information management Learning systems

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Millimeter Wave Full-Duplex Networks: MAC Design and Throughput Optimization

arXiv

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arXiv 2023年

作者： Liu, Shengbo Wu, Wen Fu, Liqun Qu, Kaige Ye, Qiang Zhuang, Weihua Shen, Sherman Frontier Research Center Peng Cheng Laboratory Shenzhen China School of Informatics Xiamen University Xiamen China Department of Electrical and Computer Engineering University of Waterloo Waterloo Canada Department of Computer Science Memorial University of Newfoundland St. John’s Canada

Full-duplex (FD) technique can remarkably boost the network capacity in the millimeter wave (mmWave) bands by enabling simultaneous transmission and reception. However, due to directional transmission and large bandwidth, the throughput and fairness performance of a mmWave FD network are affected by deafness and directional hidden-node (HN) problems and severe residual self-interference (RSI). To address these challenges, this paper proposes a directional FD medium access control protocol, named DFDMAC to support typical directional FD transmission modes by exploiting FD to transmit control frames to reduce signaling overhead. Furthermore, a novel busy-tone mechanism is designed to avoid deafness and directional HN problems and improve fairness of channel access. To reduce the impact of RSI on link throughput, we formulate a throughput maximization problem for different FD transmission modes and propose a power control algorithm to obtain the optimal transmit power. Simulation results show that the proposed DFDMAC can improve the network throughput and fairness by over 60% and 32%, respectively, compared with the existing MAC protocol in IEEE 802.11ay. Moreover, the proposed power control algorithm can effectively enhance the network throughput. Copyright © 2023, The Authors. All rights reserved.

关键词： Millimeter waves

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TaxoNN: A Light-Weight Accelerator for Deep Neural Network Training

TaxoNN: A Light-Weight Accelerator for Deep Neural Network T...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Reza Hojabr Kamyar Givaki Kossar Pourahmadi Parsa Nooralinejad Ahmad Khonsari Dara Rahmati M. Hassan Najafi School of Electrical and Computer Engineering University of Tehran Tehran Iran School of Computing and Informatics University of Louisiana at Lafayette Lafayette LA USA School of Computer Sciences Institute for Research in Fundamental Sciences (IPM) Tehran Iran School of Computer Sciences Institute for Research in Fundamental Sciences (IPM) Tehran Iran School of Computing and Informatics University of Louisiana at Lafayette Lafayette LA USA

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

Emerging intelligent embedded devices rely on Deep Neural Networks (DNNs) to be able to interact with the real-world environment. This interaction comes with the ability to retrain DNNs, since environmental conditions change continuously in time. Stochastic Gradient Descent (SGD) is a widely used algorithm to train DNNs by optimizing the parameters over the training data iteratively. In this work, first we present a novel approach to add the training ability to a baseline DNN accelerator (inference only) by splitting the SGD algorithm into simple computational elements. Then, based on this heuristic approach we propose TaxoNN, a light-weight accelerator for DNN training. TaxoNN can easily tune the DNN weights by reusing the hardware resources used in the inference process using a time-multiplexing approach and low-bitwidth units. Our experimental results show that TaxoNN delivers, on average, 0.97% higher misclassification rate compared to a full-precision implementation. Moreover, TaxoNN provides 2.1× power saving and 1.65× area reduction over the state-of-the-art DNN training accelerator.

关键词： Training Hardware computer architecture Inference algorithms Artificial neural networks Feature extraction Machine learning

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Design and optimization methodology for 3D RRAM arrays

Design and optimization methodology for 3D RRAM arrays

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International Electron Devices Meeting (IEDM)

作者： Yexin Deng Hong-Yu Chen Bin Gao Shimeng Yu Shih-Chieh Wu Liang Zhao Bing Chen Zizhen Jiang Xiaoyan Liu Tuo-Hung Hou Yoshio Nishi Jinfeng Kang H.-S. Philip Wong School of Electrical and Computer Engineering and Birck Nanotechnology Center Purdue University West Lafayette IN USA Department of Electrical Engineering and Center for Integrated Systems Stanford University Stanford CA USA Institute of Microelectronics Peking University Beijing China School of Computing Informatics and Decision System Engineering Arizona State University Tempe AZ USA Department of Electronics Engineering and Institute of Electronics National Chiao Tung University Hsinchu Taiwan Stanford University Stanford CA US

3D RRAM arrays are studied at the device- and architecture-levels. The memory cell performance for a horizontal cross-point is shown experimentally to be essentially comparable to vertical pillar-around geometry. Array performances (read/write, energy, and speed) of different 3D architectures are investigated by SPICE simulation, showing horizontal stacked RRAM is superior but suffers from higher bit cost. Adopting a bi-layer pillar electrode structure is demonstrated to enlarge the array size in 3D vertical RRAM. Design guidelines are proposed for the 3D VRRAM: it shows that increasing the number of stacks of VRRAM while keeping the total bits the same, as well as scaling of feature size (F), are critical for reducing RC delay and energy consumption.

关键词： Delays computer architecture Three-dimensional displays Microprocessors Energy consumption Tin Resistance

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