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computational modeling of the Mechanical Performance of a Magnesium Stent Undergoing Uniform and Pitting Corrosion in a Remodeling Artery

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JOURNAL OF MEDICAL DEVICES-TRANSACTIONS OF THE ASME 2017年第2期11卷 021013-021013页

作者： Boland, Enda L. Grogan, James A. McHugh, Peter E. Natl Univ Ireland Galway Coll Engn & Informat Biomech Res Ctr BMEC Biomed Engn Galway H91 HX31 Ireland

Coronary stents made from degradable biomaterials such as magnesium alloy are an emerging technology in the treatment of coronary artery disease. Biodegradable stents provide mechanical support to the artery during the initial scaffolding period after which the artery will have remodeled. The subsequent resorption of the stent biomaterial by the body has potential to reduce the risk associated with long-term placement of these devices, such as in-stent restenosis, late stent thrombosis, and fatigue fracture. computational modeling such as finite-element analysis has proven to be an extremely useful tool in the continued design and development of these medical devices. What is lacking in computational modeling literature is the representation of the active response of the arterial tissue in the weeks and months following stent implantation, i.e., neointimal remodeling. The phenomenon of neointimal remodeling is particularly interesting and significant in the case of biodegradable stents, when both stent degradation and neointimal remodeling can occur simultaneously, presenting the possibility of a mechanical interaction and transfer of load between the degrading stent and the remodeling artery. In this paper, a computational modeling framework is developed that combines magnesium alloy degradation and neointimal remodeling, which is capable of simulating both uniform (best case) and localized pitting (realistic) stent corrosion in a remodeling artery. The framework is used to evaluate the effects of the neointima on the mechanics of the stent, when the stent is undergoing uniform or pitting corrosion, and to assess the effects of the neointimal formation rate relative to the overall stent degradation rate (for both uniform and pitting conditions).

关键词： computational modeling biodegradable stent neointimal remodeling

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Factors Mediating Learning and Application of computational modeling by Life Scientists

Factors Mediating Learning and Application of Computational ...

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Frontiers in Education (FIE) Conference

作者： Aasakiran Madamanchi Monica E. Cardella James A. Glazier David M. Umulis Department of Agricultural & Biological Engineering Purdue University West Lafayette Indiana USA School of Engineering Purdue University West Lafayette Indiana USA Department of Intelligent Systems Engineering Biocomplexity Institute Indiana University Bloomington Indiana USA

ISBN: (纸本)9781538611753;9781538611746

This Work-in-Progress paper in the Research Category uses a retrospective mixed-methods study to better understand the factors that mediate learning of computational modeling by life scientists. Key stakeholders, including leading scientists, universities and funding agencies, have promoted computational modeling to enable life sciences research and improve the translation of genetic and molecular biology high-throughput data into clinical results. Software platforms to facilitate computational modeling by biologists who lack advanced mathematical or programming skills have had some success, but none has achieved widespread use among life scientists. Because computational modeling is a core engineering skill of value to other STEM fields, it is critical for engineering and computer science educators to consider how we help students from across STEM disciplines learn computational modeling. Currently we lack sufficient research on how best to help life scientists learn computational *** address this gap, in 2017, we observed a short-format summer course designed for life scientists to learn computational modeling. The course used a simulation environment designed to lower programming barriers. We used semi-structured interviews to understand students' experiences while taking the course and in applying computational modeling after the course. We conducted interviews with graduate students and post-doctoral researchers who had completed the course. We also interviewed students who took the course between 2010 and 2013. Among these past attendees, we selected equal numbers of interview subjects who had and had not successfully published journal articles that incorporated computational modeling. This Work-in-Progress paper applies social cognitive theory to analyze the motivations of life scientists who seek training in computational modeling and their attitudes towards computational modeling. Additionally, we identify important social and environmental variable

关键词： computational modeling Training Interviews Biology Programming profession Mathematical model

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Patient-Specific Cardiac computational modeling Based on Left Ventricle Segmentation from Magnetic Resonance Images 1st

Patient-Specific Cardiac Computational Modeling Based on Lef...

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1st International Conference on Data Engineering and Communication Technology (ICDECT)

作者： Bhan, Anupama Bathla, Disha Goyal, Ayush Amity Univ Uttar Pradesh Noida 201313 Uttar Pradesh India

ISBN: (纸本)9789811016783;9789811016776

This paper presents three-dimensional computational modeling of the heart's left ventricle extracted and segmented from cardiac MRI. This work basically deals with the fusion of segmented left ventricle, which is segmented using region growing method, with the generic deformable template. The multi-frame cardiac MRI image data of heart patients is taken into account. The region-based segmentation is performed in ITK-SNAP. The left ventricle is segmented in all slices in multi-frame MRI data of the whole cardiac cycle for each patient. Various parameters like myocardial muscle thickness can be calculated, which are useful for assessing cardiac function and health of a patient's heart by medical practitioners. With the left ventricle cavity and myocardium segmented, measurement of the average distance from the endocardium to the epicardium can be used to measure myocardial muscle thickness.

关键词： Patient-specific Cardiac model computational modeling Left ventricle Segmentation Magnetic resonance images

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I_Ks computational modeling to Enforce the Investigation of D242N, a K_V7.1 LQTS Mutation 44

I<sub>Ks</sub> Computational Modeling to Enforce the Investi...

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44th Computing in Cardiology Conference (CinC)

作者： Bartolucci, Chiara Moreno, Cristina Oliveras, Anna Munoz, Carmen de la Cruz, Alicia Peraza, Diego A. Gimeno, Juan R. Martin-Martinez, Mercedes Severi, Stefano Felipe, Antonio Lambiase, Pier D. Gonzalez, Teresa Valenzuela, Carmen Univ Bologna Bologna Italy UAM CSIC Inst Invest Biomed Alberto Sols Madrid Spain Univ Barcelona Barcelona Spain Hosp Univ Virgen Arrixaca Murcia El Palmar Spain CSIC Inst Quim Med Madrid Spain UCL London England

ISBN: (纸本)9781538645550;9781538666302

A KCNQ1 mutation, D242N, was found in a pair of twins and characterized at the cellular level. To investigate whether and how the mutation causes the clinically observed lost adaptation to fast heart rate, we performed a computational study. Firstly, we identified a new I-Ks model based on voltage clamp experimental data. Then we included this formulation in the human action potential model of O'Hara Rudy (ORd) and simulated the effects of the mutation. We also included adrenergic stimulation to the action potential, since the basal adrenergic tone is likely to affect the influence of I-Ks on QTc in vivo. Finally, we simulated the pseudo-ECG, taking into account the heterogeneity of the cardiac wall. At the basal rate (60bpm), the mutation had negligible effects for all cell types, whereas at the high rate (180bpm), with concomitant beta-adrenergic stimulation (mimicking exercise conditions), the mutant AP failed to adapt its duration to the same extent as the wild-type AP (e.g. 281ms vs. 267ms in M cells), due to a smaller amount of I-Ks current. Pseudo-ECG results show only a slight rate adaptation, and the simulated QTc was significantly prolonged from 387ms to 493ms, similar to experimental recordings.

关键词： computational modeling Mathematical model Heart rate Adaptation models Biological system modeling Data models Action potentials

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Emergence of Metastable Dynamics in Functional Brain Organization via Spontaneous fMRI Signal and Whole-Brain computational modeling 39

Emergence of Metastable Dynamics in Functional Brain Organiz...

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39th Annual International Conference of the IEEE-Engineering-in-Medicine-and-Biology-Society (EMBC)

作者： Lee, Won Hee Frangou, Sophia Icahn Sch Med Mt Sinai Dept Psychiat New York NY 10029 USA

ISBN: (纸本)9781509028092

Little is known about the mechanisms underlying the resting-state brain organization. This study investigated how metastability, defined as the standard deviation of synchrony described by the Kuramoto order parameter, arises from the structural connectome and relates to empirical measures of metastability in resting-state brain networks. We tested whether spontaneous fMRI brain activity in the functional organization of the human brain operates in a metastable state. We compared between empirical metastability defined in four major resting-state brain networks - auditory network, default mode network, left and right executive control networks - and simulated metastability derived from the Kuramoto model constrained by the empirical anatomical connectivity. Our results show that maximal metastability within resting-state brain networks arises from the model with different coupling strengths. Empirical metastability corresponds to a dynamical region where the simulated metastability is maximized. The emergence of metastable dynamics observed in empirical resting-state functional networks around the region of maximal metastability suggests that such a dynamical regime in the brain may drive the resting state of the brain. Our study may provide a mechanistic explanation of the origin of functional organization of the brain, and may help our understanding of the mechanistic causes of disease.

关键词： Organizations Brain modeling Standards organizations Couplings Time series analysis computational modeling Diffusion tensor imaging

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computational modeling of the immune response to yellow fever

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JOURNAL OF computational AND APPLIED MATHEMATICS 2016年 295卷 127-138页

作者： Bonin, C. R. B. dos Santos, R. W. Fernandes, G. C. Lobosco, M. Univ Fed Juiz de Fora Postgrad Program Computat Modeling BR-36036900 Juiz De Fora MG Brazil Univ Fed Juiz de Fora Sch Med BR-36036900 Juiz De Fora MG Brazil Presidente Antonio Carlos Juiz De Fora MG Brazil

Yellow fever (YF) is an infectious disease caused by a type of virus called flavivirus. According to the World Health Organization (WHO), 44 countries are endemics, and around 200,000 cases of YF are recorded per year causing 30,000 deaths, mainly in Africa and South America. For this reason, it is very important to understand the behavior of the disease and the associated immune response in order to design better strategies for treating it. To this end, this study describes a mathematical model to represent the human immune response to an infection by YF virus. For the best of our knowledge, this is the first mathematical model of the effects of the YF in the immune system. This is the beginning of a path that will allow us to verify, for example, if a booster dose of YF vaccine is really necessary every 10 years and if a lower dosage could be used to achieve similar protection. (C) 2015 Elsevier B.V. All rights reserved.

关键词： computational modeling Immune system computational immunology Ordinary differential equations Yellow fever

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computational modeling of Li-ion batteries

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computational MECHANICS 2016年第6期58卷 889-909页

作者： Grazioli, D. Magri, M. Salvadori, A. Univ Brescia DICATAM Via Branze 43 I-25123 Brescia Italy Delft Univ Technol Fac Civil Engn & Geosci POB 5048 NL-2600 GA Delft Netherlands Univ Notre Dame Dept Aerosp & Mech Engn Cushing Hall Engn Notre Dame IN 46556 USA

This review focuses on energy storage materials modeling, with particular emphasis on Li-ion batteries. Theoretical and computational analyses not only provide a better understanding of the intimate behavior of actual batteries under operational and extreme conditions, but they may tailor new materials and shape new architectures in a complementary way to experimental approaches. modeling can therefore play a very valuable role in the design and lifetime prediction of energy storage materials and devices. Batteries are inherently multi-scale, in space and time. The macro-structural characteristic lengths (the thickness of a single cell, for instance) are order of magnitudes larger than the particles that form the microstructure of the porous electrodes, which in turn are scale-separated from interface layers at which atomistic intercalations occur. Multi-physics modeling concepts, methodologies, and simulations at different scales, as well as scale transition strategies proposed in the recent literature are here revised. Finally, computational challenges toward the next generation of Li-ion batteries are discussed.

关键词： Energy storage materials computational modeling Li-ion batteries

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computational modeling of structure formation during dielectrophoresis in particulate composites

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computational MATERIALS SCIENCE 2016年第PartA期112卷 139-146页

作者： Gutierrez, M. A. Khanbareh, H. van der Zwaag, S. Delft Univ Technol Fac Aerosp Engn Novel Aerosp Mat Grp NL-2629 HS Delft Netherlands Ampelmann Operat NL-2629 HS Delft Netherlands Mat Innovat Inst M2i NL-2628 XG Delft Netherlands

In this paper a novel numerical model is proposed for qualitative simulation of the structure formation during dielectrophoresis in a medium of dielectric particles suspended in a liquid between parallelplate electrodes. Upon application of an electric field particles reorient with respect to the imposed electric field, followed by rotational and axial displacement of particles interaction until chains are formed. The performance of the model is illustrated in a number of fundamental cases. The influence of parameters such as size, aspect ratio and heterogeneity of the particles is studied for the purpose of obtaining insight in the ideal conditions required to obtain the desired structure. In a multi-particle system, the relative particle size is shown to be a key parameter in chain evolution process. The quality of the structure evolution is investigated using a set of geometric parameters. A new topological parameter, chain perfection degree, relating the microstructure to the overall performance of the piezoelectric composite, is proposed and calculated for the fundamental case-studies. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Dielectrophoretic structuring computational modeling Particulate composites

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computational modeling and Validation of Aerosol Deposition in Ventilation Ducts

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FIRE TECHNOLOGY 2016年第1期52卷 149-166页

作者： Overholt, Kristopher J. Floyd, Jason E. Ezekoye, Ofodike A. NIST 100 Bur DrMail Stop 8661 Gaithersburg MD 20899 USA Hughes Associates Inc 3610 Commerce DrSuite 817 Baltimore MD 21227 USA Univ Texas Austin Dept Mech Engn 204 E Dean Keeton St Austin TX 78712 USA

In fire models, the accurate prediction of aerosol and soot concentrations in the gas phase and their deposition thicknesses in the condensed phase is important for a wide range of applications, including human egress calculations, heat transfer in compartment fires, and forensic reconstructions. During a fire, in addition to soot transport by advection and diffusion, a significant amount of soot can be deposited on surfaces due to various mechanisms. As a first approach of quantifying aerosol deposition predictions under non-reacting flow conditions, this study identifies important parameters under various flow conditions and compares predicted aerosol deposition quantities to experimentally measured data. The computational tool used in this study was the computational fluid dynamics code, Fire Dynamics Simulator (FDS). Model predictions are compared to measured deposition velocities for various sizes of monodisperse fluorescent particles and various air velocities at the ceiling, wall, and floor of a ventilation duct.

关键词： Aerosol deposition CFD modeling Gravitational settling computational modeling

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computational modeling of megakaryocytic differentiation of umbilical cord blood-derived stem/progenitor cells

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COMPUTERS & CHEMICAL ENGINEERING 2016年 94卷 117-127页

作者： Hatami, Javad Ferreira, Frederico Castelo da Silva, Claudia L. Tiago, Jorge Sequeira, Adelia Univ Lisbon Inst Super Tecn Dept Bioengn Ave Rovisco Pais 1 P-1049001 Lisbon Portugal Univ Lisbon Inst Super Tecn iBB Ave Rovisco Pais 1 P-1049001 Lisbon Portugal Univ Lisbon Inst Super Tecn Dept Math Ave Rovisco Pais 1 P-1049001 Lisbon Portugal Univ Lisbon Inst Super Tecn CEMAT Ave Rovisco Pais 1 P-1049001 Lisbon Portugal

Quantifying the effect of exogenous parameters regulating megakaryopoiesis would enhance the design of robust and efficient protocols to produce platelets. We developed a computational model based on time-dependent ordinary differential equations (ODEs) which decoupled expansion and differentiation kinetics of cells using a subpopulation dynamic model. The model described umbilical cord blood (UCB)-derived cell's behavior in response to the external stimuli during expansion and megakaryocytic differentiation ex vivo. We observed that the rate of expansion of Mk progenitors and production of mature Mks were higher when TPO was included in the expansion cytokine cocktail and TPO and IL-3 were added during differentiation stage. Our computational approach suggests that the Mk progenitors were an important intermediate population that their dynamic should be optimized in order to establish an efficient protocol. This model provides important insights into dynamics of cell subpopulations during megakaryopoiesis process and could potentially contribute towards the rational design of cell-based therapy bioprocesses. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Hematopoietic stem/progenitor cells Umbilical cord blood computational modeling Megakaryocyte Platelet

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