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18th European Conference on Composite Materials, ECCM 2018

作者： Straumit, I. Baran, I. Gorbatikh, L. Farkas, L. Hahn, C. Ilin, K. Ivens, J. Lessard, L. Liu, Y. Nguyen, N. Matveeva, A. Mehdikhani, M. Shishkina, O. Soete, J. Takahashi, J. Vandepitte, D. Vasiukov, D. Wan, Y. Winterstein, E. Wevers, M. Lomov, S.V. Department of Materials Engineering KU Leuven Belgium Chair of Production Technology Faculty of Engineering Technology University of Twente Netherlands Siemens Industry Software NV Leuven Belgium Germany Department of Mechanical Engineering McGill University Montreal Canada Polymers and Composites Technology and Mechanical Engineering Department IMT Lille Douai France SIM M3 program Technologiepark 935 ZwijnaardeB-9052 Belgium Department of Systems Innovation University of Tokyo Japan Department of Mechanical Engineering KU Leuven Belgium

ISBN: (纸本)9781510896932

The paper presents an overview of cases in which the analysis of the internal structure and mechanical properties of fibre reinforced composites is performed based on the micro-computed X-ray tomography (micro-CT) reconstruction of the composite reinforcement geometry. In all the cases, the analysis relies on structure tensor-based algorithms for quantification of the micro-CT image, implemented in VoxTex software. © CCM 2020 - 18th European Conference on Composite Materials. All rights reserved.

关键词： Computerized tomography

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Wernicke Encephalopathy After Roux-en-Y Gastric Bypass Presenting with Altered Mental Status—A Video Case Report

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Obesity Surgery 2024年第6期34卷 2271-2273页

作者： Chen, Chih-Chiang Chang, Po-Chih Chang, Ting-Wei Chuang, Hui-Yu Department of Surgery Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung City Taiwan School of Medicine College of Medicine National Sun Yat-sen University Kaohsiung City Taiwan Division of Thoracic Surgery Department of Surgery Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung City Taiwan Weight Management Center Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung City Taiwan Department of Sports Medicine College of Medicine Kaohsiung Medical University Kaohsiung City Taiwan Ph. D. Program in Biomedical Engineering College of Medicine Kaohsiung Medical University Kaohsiung City Taiwan Department of Obstetrics and Gynecology Kaohsiung Medical University Hospital Kaohsiung Medical University No. 100 Tzyou 1st Road Kaohsiung City 80756 Taiwan

Wernicke encephalopathy (WE) is a seldom encountered yet significant neuropsychiatric ailment resulting from a deficiency in thiamine (vitamin B1). While commonly linked with chronic alcoholism or insufficient dietary intake, instances of WE following bariatric and metabolic surgeries, notably laparoscopic Roux-en-Y gastric bypass (RYGB), have been sporadically documented. This case study elucidates the condition of a male patient who, 3 months after undergoing RYGB to address severe obesity, displayed abrupt alterations in mental status, swiftly ameliorated by immediate administration of intravenous high-dose thiamine. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Laparoscopic Roux-en-Y gastric bypass Severe obesity Wernicke encephalopathy

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Self-assembly of nanotubes from distinct gamma-modified peptide nucleic acid oligomers in organic solvent mixtures 17

Self-assembly of nanotubes from distinct gamma-modified pept...

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17th Annual Conference on Foundations of Nanoscience: Self-Assembled Architectures and Devices, FNANO 2020

作者： Kumar, Shram Pearse, Alexander Liu, Ying Taylor, Rebecca E. Department of Mechanical Engineering Carnegie Mellon University Pittsburgh United States Department of Chemistry Carnegie Mellon University Pittsburgh United States Department of Biomedical Engineering Carnegie Mellon University Pittsburgh United States Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh United States

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BP-ExerGuide: Smart Blood Pressure Monitor System for Personalized Exercise Safety Guidelines in Senior Communities

BP-ExerGuide: Smart Blood Pressure Monitor System for Person...

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IEEE Eurasia Conference on biomedical engineering, Healthcare and Sustainability (ECBIOS)

作者： Yu-Sheng Lin Chih-Chun Lin Guan-Wei Huang Jing-Peng Wu Li-Chieh Kuo Fong-Chin Su Yi-Ching Yang Department of Mechanical Engineering Southern Taiwan University of Science and Technology Tainan City Taiwan Medical Device Innovation Center National Cheng Kung University Tainan City Taiwan Department of Physical Therapy I-Shou University Kaohsiung City Taiwan Department of Occupational Therapy National Cheng Kung University Tainan City Taiwan Department of Biomedical Engineering National Cheng Kung University Tainan City Taiwan Department of Family Medicine National Cheng Kung University Hospital Tainan City Taiwan

Hypertension is highly prevalent among older adults, and its global incidence is increasing primarily due to the aging population. With the development of information and communication technology, smart blood pressure monitors have been developed to offer more personalized guidance to users. A smart blood pressure monitor must provide users with professional guidance, such as monitoring pregnancy-induced hypertension for pregnant women and brain health indicators for older adults. This increases user willingness and engagement. In this study, we developed a smart blood pressure monitor system called “BP-ExerGuide” to provide a personalized exercise safety guideline for older adults in the community's smart gym. In this scenario, all smart gym devices are equipped with RFID sensors, and members can use their personal RFID cards to start a blood pressure measurement. Only when the blood pressure value meets the safety criteria for exercise, can they use the exercise devices. If an individual's blood pressure is too high, BP-ExerGuide acts like a sports coach, advising seniors to take a rest first and then start exercising once they meet the safety guidelines. The system also integrates exercise logs and blood pressure logs into a smart healthcare platform for seniors to track their physiological changes. Overall, the BP-ExerGuide system provides older adults with a safer and more personalized exercise experience while monitoring their blood pressure levels. This system improves the willingness of seniors to exercise regularly and thus promotes better health and well-being.

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Small metal artifact detection and inpainting in cardiac CT images

arXiv

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arXiv 2024年

作者： McKeown, Trevor Michael Gach, H. Hao, Yao An, Hongyu Robinson, Clifford G. Cuculich, Phillip S. Yang, Deshan Medical Physics Program Duke University United States Department of Radiation Oncology Duke University United States Department of Radiation Oncology School of Medicine Washington University in Saint Louis United States Department of Radiology School of Medicine Washington University in Saint Louis United States Department of Biomedical Engineering Washington University in Saint Louis United States Department of Cardiology School of Medicine Washington University in Saint Louis United States

Background: Quantification of cardiac motion on pre-treatment CT imaging for stereotactic arrhythmia radiotherapy patients is difficult due to the presence of image artifacts caused by metal leads of implantable cardioverter-defibrillators (ICDs). The CT scanners’ onboard metal artifact reduction tool does not sufficiently reduce these artifacts. More advanced artifact reduction techniques require the raw CT projection data and thus are not applicable to already reconstructed CT images. New methods are needed to accurately reduce the metal artifacts in already reconstructed CTs to recover the otherwise lost anatomical information. Purpose: To develop a methodology to automatically detect metal artifacts in cardiac CT scans and inpaint the affected volume with anatomically consistent structures and values. Methods: Breath-hold ECG-gated 4DCT scans of 12 patients who underwent cardiac radiation therapy for treating ventricular tachycardia were collected. The metal artifacts in the images caused by the ICD leads were manually contoured. A 2D U-Net deep learning (DL) model was developed to segment the metal artifacts automatically using eight patients for training, two for validation, and two for testing. A dataset of 592 synthetic CTs was prepared by adding segmented metal artifacts from the patient 4DCT images to artifact-free cardiac CTs of 148 patients. A 3D image inpainting DL model was trained to refill the metal artifact portion in the synthetic images with realistic image contents that approached the ground truth artifact-free images. The trained inpainting model was evaluated by analyzing the automated segmentation results of the four heart chambers with and without artifacts on the synthetic dataset. Additionally, the raw cardiac patient images with metal artifacts were processed using the inpainting model and the results of metal artifact reduction were qualitatively inspected. Results: The artifact detection model worked well and produced a Dice score of 0.9

关键词： Computerized tomography

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k-mer-based approaches to bridging pangenomics and population genetics

arXiv

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arXiv 2024年

作者： Roberts, Miles D. Davis, Olivia Josephs, Emily B. Williamson, Robert J. Genetics and Genome Sciences Program Michigan State University East LansingMI48824 United States Department of Computer Science and Software Engineering Rose-Hulman Institute of Technology Terre HauteIN47803 United States Department of Biology and Biomedical Engineering Rose-Hulman Institute of Technology Terre HauteIN47803 United States Department of Plant Biology Michigan State University East LansingMI48824 United States Ecology Evolution and Behavior Program Michigan State University East LansingMI48824 United States Plant Resilience Institute Michigan State University East LansingMI48824 United States

Many commonly studied species now have more than one chromosome-scale genome assembly, revealing a large amount of genetic diversity previously missed by approaches that map short reads to a single reference. However, many species still lack multiple reference genomes and correctly aligning references to build pangenomes is challenging, limiting our ability to study this missing genomic variation in population genetics. Here, we argue that k-mers are a crucial stepping stone to bridging the reference-focused paradigms of population genetics with the reference-free paradigms of pangenomics. We review current literature on the uses of k-mers for performing three core components of most population genetics analyses: identifying, measuring, and explaining patterns of genetic variation. We also demonstrate how different k-mer-based measures of genetic variation behave in population genetic simulations according to the choice of k, depth of sequencing coverage, and degree of data compression. Overall, we find that k-mer-based measures of genetic diversity scale consistently with pairwise nucleotide diversity (π) up to values of about π = 0.025 (R2 = 0.97) for neutrally evolving populations. For populations with even more variation, using shorter k-mers will maintain the scalability up to at least π = 0.1. Furthermore, in our simulated populations, k-mer dissimilarity values can be reliably approximated from counting bloom filters, highlighting a potential avenue to decreasing the memory burden of k-mer based genomic dissimilarity analyses. For future studies, there is a great opportunity to further develop methods to identifying selected loci using k-mers. © 2024, CC BY.

关键词： Genome

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Discovery of high-entropy ceramics via machine learning

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npj Computational Materials 2020年第1期6卷 1323-1331页

作者： Kevin Kaufmann Daniel Maryanovsky William M.Mellor Chaoyi Zhu Alexander S.Rosengarten Tyler J.Harrington Corey Oses Cormac Toher Stefano Curtarolo Kenneth S.Vecchio Department of NanoEngineering UC San DiegoLa JollaCA 92093USA Department of Cognitive Science UC San DiegoLa JollaCA 92093USA Materials Science and Engineering Program UC San DiegoLa JollaCA 92093USA Department of Mechanical Engineering and Materials Science Duke UniversityDurhamNC 27708USA Materials Science Electrical EngineeringPhysics and ChemistryDuke UniversityDurhamNC 27708USA

Although high-entropy materials are attracting considerable interest due to a combination of useful properties and promising applications,predicting their formation remains a hindrance for rational discovery of new *** approaches are based on physical intuition and/or expensive trial and error *** computational methods rely on the availability of sufficient experimental data and computational *** learning(ML)applied to materials science can accelerate development and reduce *** this study,we propose an ML method,leveraging thermodynamic and compositional attributes of a given material for predicting the synthesizability(i.e.,entropy-forming ability)of disordered metal carbides.

关键词： ceramics entropy attracting

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A Sparse DAE Solver in Maple

arXiv

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arXiv 2022年

作者： Jang, Taejin Uppaluri, Maitri Subramanian, Venkat R. Materials Science and Engineering Program Texas Materials Institute The University of Texas at Austin AustinTX78712 United States Walker Department of Mechanical Engineering The University of Texas at Austin AustinTX78712 United States Oden Institute for Computational Science and Engineering The University of Texas at Austin AustinTX United States

In this paper, some adaptive single-step methods like Trapezoid (TR), Implicit-mid point (IMP), Euler-backward (EB), and Radau IIA (Rad) methods are implemented in Maple to solve index-1 nonlinear Differential Algebraic Equations (DAEs). Maple's robust and efficient ability to search within a list/set is exploited to identify the sparsity pattern and the analytic Jacobian. The algorithm and implementation were found to be robust and efficient for index-1 DAE problems and scales well for finite difference/finite element discretization of two-dimensional models with system size up to 10,000 nonlinear DAEs and solves the same in few seconds. © 2022, CC BY-NC-ND.

关键词： Differential equations

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Characterizing the mechanical response of metallic glasses to uniaxial tension using a spring network model

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Physical Review Materials 2023年第7期7卷 073605-073605页

作者： Aya Nawano Weiwei Jin Jan Schroers Mark D. Shattuck Corey S. O'Hern Department of Mechanical Engineering and Materials Science Yale University New Haven Connecticut 06520 USA Benjamin Levich Institute and Physics Department The City College of New York New York New York 10031 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA Graduate Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA

A coarse-grained spring network model is proposed for the prediction of the mechanical response of metallic glasses as a function of the microstructure prior to loading. This model describes the mechanical response of metallic glasses using a network of parallel springs that can break and reform, mimicking atomic rearrangements during deformation. We compare predictions of the spring network model for stress versus strain to results from numerical simulations of athermal quasistatic, uniaxial tensile deformation of Cu50Zr50 metallic glasses using Lennard-Jones (LJ) and embedded atom method (EAM) atomic interactions. We show that both the LJ and EAM models possess qualitatively similar stress σ versus strain γ curves. By specifying five parameters [ultimate strength, strain at ultimate strength, slopes of σ(γ) at γ=0 and at large strain, and strain at fracture where σ=0], we demonstrate that the spring network model can accurately describe the form of the stress-strain curves during uniaxial tension for the computational studies of Cu50Zr50, as well as recent experimental studies of several Zr-based metallic glasses.

关键词： Alloys Amorphous materials Glasses Packing & jamming problems Molecular dynamics

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Deep Reinforcement Learning Applied to a Sparse-Reward Trading Environment with Intraday Data

SSRN

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SSRN 2023年

作者： Takara, Lucas de Azevedo Alves Portela Santos, André Mariani, Viviana Cocco dos Santos Coelho, Leandro Department of Electrical Engineering PPGEE Federal University of Parana UFPR Avenida Coronel Francisco Herácito dos Santos Parana Curitiba81530–000 Brazil CUNEF Universidad Calle Almansa 101 Madrid28040 Spain Mechanical Engineering Graduate Program PPGEM Pontifical Catholic University of Parana PUCPR Imaculada Conceição Parana Curitiba80215–901 Brazil Industrial and Systems Engineering Graduate Program PPGEPS Pontifical Catholic University of Parana PUCPR Imaculada Conceição Parana Curitiba80215–901 Brazil

Deep reinforcement learning (DRL) achieved significant progress in several areas enabling computers to perform complex decision-making tasks. Applied to quantitative trading, DRL trading agents can optimize their decisions during distinct market scenarios to reach a profitable strategy by learning from previous experiences. This work proposes a trading system containing a variant of the Deep Q-Network (DQN) algorithm as its main component called Extended Trading DQN (ETDQN). It can adapt its learning to trade across numerous market-behavior moments, receiving feedback only when a trade is liquidaded, differently from recent approaches that provide constant feedback. Based on distributional learning and other independent extensions suggested by the DRL community, the algorithm optimizes its decision-making process by replaying prioritized experiences containing different sub-goals, assisting the agent in collecting the maximum value of profits and removing the need for fine-tuning rewards. ETDQN learned to trade on three distinct financial time series signals, identifying trading opportunities during volatile price moments. The algorithm showed more aggressive behavior regarding the volatility of its annual returns than the Trading DQN benchmark, achieving a 1.46 and 7.13 better performance with respect to average daily cumulative returns in Western Digital Corporation and Cosmos cryptocurrency historical market data. © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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