June 14, 2021

Download Ebook Free Personalized Computational Hemodynamics

Personalized Computational Hemodynamics

Personalized Computational Hemodynamics
Author : Yuri Vassilevski,Maxim Olshanskii,Sergey Simakov,Andrey Kolobov,Alexander Danilov
Publisher : Academic Press
Release Date : 2020-04-19
Category : Science
Total pages :280
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Personalized Computational Hemodynamics: Models, Methods, and Applications for Vascular Surgery and Antitumor Therapy offers practices and advances surrounding the multiscale modeling of hemodynamics and their personalization with conventional clinical data. Focusing on three physiological disciplines, readers will learn how to derive a suitable mathematical model and personalize its parameters to account for pathologies and diseases. Written by leading experts, this book mirrors the top trends in mathematical modeling with clinical applications. In addition, the book features the major results of the "Research group in simulation of blood flow and vascular pathologies" at the Institute of Numerical Mathematics of the Russian Academy of Sciences. Two important features distinguish this book from other monographs on numerical methods for biomedical applications. First, the variety of medical disciplines targeted by the mathematical modeling and computer simulations, including cardiology, vascular neurology and oncology. Second, for all mathematical models, the authors consider extensions and parameter tuning that account for vascular pathologies. Examines a variety of medical disciplines targeted by mathematical modeling and computer simulation Discusses how the results of numerical simulations are used to support clinical decision-making Covers hemodynamics relating to various subject areas, including vascular surgery and oncological tumor treatments

Patient-specific Hemodynamic Computations: Application to Personalized Diagnosis of Cardiovascular Pathologies

Patient-specific Hemodynamic Computations: Application to Personalized Diagnosis of Cardiovascular Pathologies
Author : Lucian Mihai Itu,Puneet Sharma,Constantin Suciu
Publisher : Springer
Release Date : 2017-05-31
Category : Medical
Total pages :227
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Hemodynamic computations represent a state-of-the-art approach for patient-specific assessment of cardiovascular pathologies. The book presents the development of reduced-order multiscale hemodynamic models for coronary artery disease, aortic coarctation and whole body circulation, which can be applied in routine clinical settings for personalized diagnosis. Specific parameter estimation frameworks are introduced for calibrating the parameters of the models and high performance computing solutions are employed to reduce their execution time. The personalized computational models are validated against patient-specific measurements. The book is written for scientists in the field of biomedical engineering focusing on the cardiovascular system, as well as for research-oriented physicians in cardiology and industrial players in the field of healthcare technologies.

Patient-specific Hemodynamic Computations: Application to Personalized Diagnosis of Cardiovascular Pathologies

Patient-specific Hemodynamic Computations: Application to Personalized Diagnosis of Cardiovascular Pathologies
Author : Lucian Mihai Itu,Puneet Sharma,Constantin Suciu
Publisher : Springer
Release Date : 2018-08-12
Category : Medical
Total pages :227
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Hemodynamic computations represent a state-of-the-art approach for patient-specific assessment of cardiovascular pathologies. The book presents the development of reduced-order multiscale hemodynamic models for coronary artery disease, aortic coarctation and whole body circulation, which can be applied in routine clinical settings for personalized diagnosis. Specific parameter estimation frameworks are introduced for calibrating the parameters of the models and high performance computing solutions are employed to reduce their execution time. The personalized computational models are validated against patient-specific measurements. The book is written for scientists in the field of biomedical engineering focusing on the cardiovascular system, as well as for research-oriented physicians in cardiology and industrial players in the field of healthcare technologies.

Computational Fluid Dynamics Indicators to Improve Cardiovascular Pathologies

Computational Fluid Dynamics Indicators to Improve Cardiovascular Pathologies
Author : Eduardo Soudah Prieto
Publisher : Unknown
Release Date : 2016
Category :
Total pages :181
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In recent years, the study of computational hemodynamics within anatomically complex vascular regions has generated great interest among clinicians. The progress in computational fluid dynamics, image processing and high-performance computing haveallowed us to identify the candidate vascular regions for the appearance of cardiovascular diseases and to predict how this disease may evolve. Medicine currently uses a paradigm called diagnosis. In this thesis we attempt to introduce into medicine the predictive paradigm that has been used in engineering for many years. The objective of this thesis is therefore to develop predictive models based on diagnostic indicators for cardiovascular pathologies. We try to predict the evolution of aortic abdominal aneurysm, aortic coarctation and coronary artery disease in a personalized way for each patient. To understand how the cardiovascular pathology will evolve and when it will become a health risk, it is necessary to develop new technologies by merging medical imaging and computational science. We propose diagnostic indicators that can improve the diagnosis and predict the evolution of the disease more efficiently than the methods used until now. In particular, a new methodology for computing diagnostic indicators based on computational hemodynamics and medical imaging is proposed. We have worked with data of anonymous patients to create real predictive technology that will allow us to continue advancing in personalized medicine and generate more sustainable health systems. However, our final aim is to achieve an impact at a clinical level. Several groups have tried to create predictive models for cardiovascular pathologies, but they have not yet begun to use them in clinical practice. Our objective is to go further and obtain predictive variables to be used practically in the clinical field. It is to be hoped that in the future extremely precise databases of all of our anatomy and physiology will be available to doctors. These data can be used for predictive models to improve diagnosis or to improve therapies or personalized treatments.

Patient-Specific Modeling of the Cardiovascular System

Patient-Specific Modeling of the Cardiovascular System
Author : Roy C.P. Kerckhoffs
Publisher : Springer Science & Business Media
Release Date : 2010-09-03
Category : Science
Total pages :240
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Peter Hunter Computational physiology for the cardiovascular system is entering a new and exciting phase of clinical application. Biophysically based models of the human heart and circulation, based on patient-specific anatomy but also informed by po- lation atlases and incorporating a great deal of mechanistic understanding at the cell, tissue, and organ levels, offer the prospect of evidence-based diagnosis and treatment of cardiovascular disease. The clinical value of patient-specific modeling is well illustrated in application areas where model-based interpretation of clinical images allows a more precise analysis of disease processes than can otherwise be achieved. For example, Chap. 6 in this volume, by Speelman et al. , deals with the very difficult problem of trying to predict whether and when an abdominal aortic aneurysm might burst. This requires automated segmentation of the vascular geometry from magnetic re- nance images and finite element analysis of wall stress using large deformation elasticity theory applied to the geometric model created from the segmentation. The time-varying normal and shear stress acting on the arterial wall is estimated from the arterial pressure and flow distributions. Thrombus formation is identified as a potentially important contributor to changed material properties of the arterial wall. Understanding how the wall adapts and remodels its material properties in the face of changes in both the stress loading and blood constituents associated with infl- matory processes (IL6, CRP, MMPs, etc.

Towards Personalized Models of the Cardiovascular System Using 4D Flow MRI

Towards Personalized Models of the Cardiovascular System Using 4D Flow MRI
Author : Belén Casas Garcia
Publisher : Linköping University Electronic Press
Release Date : 2019-02-15
Category :
Total pages :71
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Current diagnostic tools for assessing cardiovascular disease mostly focus on measuring a given biomarker at a specific spatial location where an abnormality is suspected. However, as a result of the dynamic and complex nature of the cardiovascular system, the analysis of isolated biomarkers is generally not sufficient to characterize the pathological mechanisms behind a disease. Model-based approaches that integrate the mechanisms through which different components interact, and present possibilities for system-level analyses, give us a better picture of a patient’s overall health status. One of the main goals of cardiovascular modelling is the development of personalized models based on clinical measurements. Recent years have seen remarkable advances in medical imaging and the use of personalized models is slowly becoming a reality. Modern imaging techniques can provide an unprecedented amount of anatomical and functional information about the heart and vessels. In this context, three-dimensional, three-directional, cine phase-contrast (PC) magnetic resonance imaging (MRI), commonly referred to as 4D Flow MRI, arises as a powerful tool for creating personalized models. 4D Flow MRI enables the measurement of time-resolved velocity information with volumetric coverage. Besides providing a rich dataset within a single acquisition, the technique permits retrospective analysis of the data at any location within the acquired volume. This thesis focuses on improving subject-specific assessment of cardiovascular function through model-based analysis of 4D Flow MRI data. By using computational models, we aimed to provide mechanistic explanations of the underlying physiological processes, derive novel or improved hemodynamic markers, and estimate quantities that typically require invasive measurements. Paper I presents an evaluation of current markers of stenosis severity using advanced models to simulate flow through a stenosis. Paper II presents a framework to personalize a reduced-order, mechanistic model of the cardiovascular system using exclusively non-invasive measurements, including 4D Flow MRI data. The modelling approach can unravel a number of clinically relevant parameters from the input data, including those representing the contraction and relaxation patterns of the left ventricle, and provide estimations of the pressure-volume loop. In Paper III, this framework is applied to study cardiovascular function at rest and during stress conditions, and the capability of the model to infer load-independent measures of heart function based on the imaging data is demonstrated. Paper IV focuses on evaluating the reliability of the model parameters as a step towards translation of the model to the clinic.

Artificial Intelligence for Computational Modeling of the Heart

Artificial Intelligence for Computational Modeling of the Heart
Author : Tommaso Mansi,Tiziano Passerini,Dorin Comaniciu
Publisher : Academic Press
Release Date : 2019-11-25
Category : Science
Total pages :274
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Artificial Intelligence for Computational Modeling of the Heart presents recent research developments towards streamlined and automatic estimation of the digital twin of a patient’s heart by combining computational modeling of heart physiology and artificial intelligence. The book first introduces the major aspects of multi-scale modeling of the heart, along with the compromises needed to achieve subject-specific simulations. Reader will then learn how AI technologies can unlock robust estimations of cardiac anatomy, obtain meta-models for real-time biophysical computations, and estimate model parameters from routine clinical data. Concepts are all illustrated through concrete clinical applications. Presents recent advances in computational modeling of heart function and artificial intelligence technologies for subject-specific applications Discusses AI-based technologies for robust anatomical modeling from medical images, data-driven reduction of multi-scale cardiac models, and estimations of physiological parameters from clinical data Illustrates the technology through concrete clinical applications and discusses potential impacts and next steps needed for clinical translation

Patient-specific Computational Models of Dyssynchronous Heart Failure and Cardiac Resynchronization Therapy for Clinical Diagnosis and Decision Support

Patient-specific Computational Models of Dyssynchronous Heart Failure and Cardiac Resynchronization Therapy for Clinical Diagnosis and Decision Support
Author : Christopher T. Villongco
Publisher : Unknown
Release Date : 2015
Category :
Total pages :191
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Dyssynchronous heart failure (DHF) is a severe form of heart failure where conduction block in the left bundle branch causes delayed left ventricular electrical activation and discoordinated systolic contraction, dramatically reducing cardiac output. Cardiac resynchronization therapy (CRT) is a cost effective pacing treatment that has been shown to improve symptoms and survival, especially due to left ventricular reverse remodeling. However, approximately 50% of patients do not show objective evidence of reverse remodeling even after 6 months of CRT. A deeper understanding of the physiological mechanisms leading to positive long-term outcomes and identification of patients who are most likely to benefit are needed to maximize quality of care and minimize health risks and economic costs. The ability to predict the outcome and personalize CRT application for an individual patient from clinical measurements alone is challenging given the wide inter-patient variability of clinical features and pathophysiological complexity of DHF. In this work, we seek to answer questions regarding physiological mechanisms that are implicated in CRT response, baseline physiological features that are predictive of response, and personalized CRT application for an individual patient. For this purpose, we construct patient-specific computational models of DHF which integrate anatomical, electrophysiological, biomechanical, and hemodynamic clinical and empirical data to quantitatively characterize baseline and CRT physiology to understand how patients differ in response. The primary aims of this thesis will be to : 1) construct patient-specific computational models of DHF incorporating clinical and empirical measurements to test whether the models can recapitulate characteristics of DHF and predict measured acute effects of CRT; 2) test the hypothesis that CRT response physiologically depends on the severity of baseline heterogeneity of mechanical loading caused by electrical dyssynchrony and ventricular dilation; 3) test the hypothesis that CRT response can be predicted from novel model-derived biomarkers of electrical dyssynchrony. Through quantification and prediction of patient-specific cardiovascular physiology in disease and therapy, computational models have great potential to enhance the quality of medical care by providing novel diagnostic value to support clinical decisions regarding the best personalized approach to treat the individual patient.

Modern Mechanobiology

Modern Mechanobiology
Author : Tzung K Hsiai,Sharon Gerecht,Hanjoong Jo,Juhyun Lee
Publisher : Unknown
Release Date : 1920-08-14
Category :
Total pages :400
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Modern mechanobiology converges both engineering and medicine to address personalized medicine. This book is built on the previously well-received edition, Hemodynamics and Mechanobiology of Endothelium. The central theme focuses on "omic" approaches to mechanosignal transduction underlying tissue development, injury, and repair. A cadre of investigators has contributed to the individual book chapters, thereby enriching the interface between mechanobiology and precision medicine for personalized diagnosis and intervention. The first two chapters provide the fundamental basis of vascular disease in response to hemodynamic shear stress. The following chapters embark on a journey of cardiovascular development and regeneration, valvular and cardiac morphogenesis, mechanosensitive microRNA and histone unfolding, computational fluid dynamics, and light-sheet imaging. The textbook represents a paradigm shift from traditional biomechanics and signal transduction to transgenic models, including novel zebrafish and chick embryos. This second edition targets a wider readership from academia to industry and government agencies in the field of mechanobiology.

A Modified Parallel Plate Flow Chamber to Study Local Endothelial Response to Recirculating Disturbed Flow

A Modified Parallel Plate Flow Chamber to Study Local Endothelial Response to Recirculating Disturbed Flow
Author : Jason Matthew Sedlak
Publisher : Unknown
Release Date : 2020
Category : Atherosclerosis
Total pages :233
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Cardiovascular disease is the leading cause of death around the world, including the stiffening of artery walls known as atherosclerosis. Atherosclerosis develops at arterial sites where endothelial cells (ECs) are exposed to low time averaged hemodynamic shear stress, particularly in regions of recirculating disturbed flow. While the effects of disturbed hemodynamics are greatly studied, the complexity of in vivo geometry and how the resulting spatial transitions between atheroprotective and atherogenic hemodynamics affect EC dysfunction are not as well understood. The core objective of this dissertation is to explore the association between local heterogeneity in blood flow and EC function, through functional phenotype assessment and correlation to computational fluid dynamics modelling of flow within a custom microfluidic device. Computational fluid dynamic (CFD) modelling informed an in vitro parallel plate flow chamber gasket modification for protruding baffles in order to produce segments of large recirculating flow contiguous with segments of steady laminar flow. After experimental validation using bovine aortic endothelial cells (BAECs), four regions of interest were identified: at the apex of the baffles (DFG-High), within the recirculation (DFG-Recirc), the low shear stress transition from DFG Recirc to DFG-Low (DFG-Low), and the center lane of moderate shear stress bulk flow which was bounded by the previous three conditions (DFG-2Pa). Then, BAECs within these regions were assessed by immunofluorescent imaging for adaption to in vitro flow via changes to morphology, cell quiescence, and monolayer permeability and junction integrity. Surprisingly, cells in disturbed flow device regions exposed to atheroprotective shear stress (DFG-2Pa) did not consistently align or decrease permeability as expected and demonstrated low levels of nitric oxide bioavailability (DFG-High & DFG-2Pa). Finally, the relationship between coordinate-specific measurements of F-actin alignment and CFD-derived shear stress features was investigated using supervised partial least square regression (PLSR) principal component analysis. In samples with an overall-low degree of alignment, shear stress magnitude contributed the most of any other variable to the PLSR model (18.9% of the 67.7% total variance in alignment explained). Conversely, in samples with an overall-high degree of alignment, the shear stress gradient components parallel and perpendicular to the net direction of flow were equally as effective compared to shear stress magnitude (12.4%, 11.8%, and 12.7%, respectively, of the 69.24% total variance in alignment explained). These results demonstrate cells in flow unexpectedly adopting a hybrid phenotype between atheroprotective and atheroprone, with post-hoc analysis suggesting local shear stress gradients play a determining role. This research supports advancing understanding of EC mechanotransduction within complex atheroma environment hemodynamics to focus research topics and develop predictive clinical diagnostic tools. Keywords: Atherosclerosis, Disturbed flow, Endothelial, Mechanotransduction, Shear stress gradient, Transverse flow

Modern Mechanobiology

Modern Mechanobiology
Author : Juhyun Lee,Sharon Gerecht,Hanjoong Jo,Tzung Hsiai
Publisher : CRC Press
Release Date : 2021-02-25
Category : Medical
Total pages :250
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Modern mechanobiology converges both engineering and medicine to address personalized medicine. This book is built on the previously well-received edition, Hemodynamics and Mechanobiology of Endothelium. The central theme is "omic" approaches to mechanosignal transduction underlying tissue development, injury, and repair. A cadre of investigators has contributed to the chapters, enriching the interface between mechanobiology and precision medicine for personalized diagnosis and intervention. The book begins with the fundamental basis of vascular disease in response to hemodynamic shear stress and then details cardiovascular development and regeneration, valvular and cardiac morphogenesis, mechanosensitive microRNA and histone unfolding, computational fluid dynamics, and light-sheet imaging. This edition represents a paradigm shift from traditional biomechanics and signal transduction to transgenic models, including novel zebrafish and chick embryos, and targets a wider readership from academia to industry and government agencies in the field of mechanobiology.

Modern Mechanobiology

Modern Mechanobiology
Author : Juhyun Lee,Sharon Gerecht,Hanjoong Jo,Tzung Hsiai
Publisher : CRC Press
Release Date : 2021-02-25
Category : Medical
Total pages :250
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Modern mechanobiology converges both engineering and medicine to address personalized medicine. This book is built on the previously well-received edition, Hemodynamics and Mechanobiology of Endothelium. The central theme is "omic" approaches to mechanosignal transduction underlying tissue development, injury, and repair. A cadre of investigators has contributed to the chapters, enriching the interface between mechanobiology and precision medicine for personalized diagnosis and intervention. The book begins with the fundamental basis of vascular disease in response to hemodynamic shear stress and then details cardiovascular development and regeneration, valvular and cardiac morphogenesis, mechanosensitive microRNA and histone unfolding, computational fluid dynamics, and light-sheet imaging. This edition represents a paradigm shift from traditional biomechanics and signal transduction to transgenic models, including novel zebrafish and chick embryos, and targets a wider readership from academia to industry and government agencies in the field of mechanobiology.

Modeling and Optimization for Pediatric Cardiovascular Surgeries

Modeling and Optimization for Pediatric Cardiovascular Surgeries
Author : Aekaansh Verma
Publisher : Unknown
Release Date : 2020
Category :
Total pages :129
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Historically, guidelines and practices in cardiovascular surgery have been developed through trial-and-error in human and animal studies. Improvements in these practices concerning overall hemodynamics in the patient require extensive experience, often gained through large clinical trials. The development of realistic patient-specific simulation capabilities offers a safe and inexpensive sand-box for rapidly testing new surgical techniques and medical devices. Recent developments in image acquisition, anatomical modeling, and predictive hemodynamics simulations have given rise to the paradigm of virtual surgical planning for cardiovascular surgeries, building on personalized treatments found in other areas of medicine. Despite these developments, clinical translation of virtual surgical planning tools have been limited by computational cost of patient-specific simulations, intractable run-times for parametric studies, and complexity of modeling cardiovascular surgery. In this thesis, I address the last two limitations, that is, reduction of run-time for design discovery, through a simulation-based optimization framework, and expansion of the current set of cardiovascular surgical modeling tools. We select the Surrogate Management Framework (SMF) is selected as the optimization framework of choice, owing to its' flexibility, ability to handle general constraints, non-smooth convergence theory, and popularity as a black-box optimizer. To reduce the SMF run-time in a high-performance computing environment, two fully concurrent variants of the SMF are developed. The trade-off between total computational expense and time-efficiency for these variants are shown for a set of analytical functions. Substantial savings in time is also obtained on a model simulation-based optimization problem. The concurrent methods also showed more robustness to choice of initialization set. The developed concurrent SMF is then applied to a problem of clinical interest: the design of a systemic-to-pulmonary shunt for the assisted bidirectional Glenn (ABG), a recently proposed alternative for stage-1 single ventricle palliation. With the goal of maximizing pulmonary flow subject to physiological Vena Caval pressure constraint, optimal pulmonary flow-SVC pressure behavior is found to depend strongly on pulmonary vascular resistance. Pulmonary vascular resistance values in neonates, assessed from literature and from a retrospective study, show theoretical viability of optimal ABG designs, as well as raise fundamental questions on existing notions of oxygen delivery in single ventricle neonates. These questions are discussed in detail with the help of lumped parameter models. Prior efforts to model complex vascular interventions in-silico have been limited to either placement of medical devices, such as stents, or to the addition or removal of whole vessels or grafts. A new direction for extending analysis-based virtual surgery modeling is presented through the example of an end-to-end resection surgery for aortic coarctation patients. A mesh generated from an anatomical model is altered directly using computational geometric operations, instead of analytical features of the model. This allows for a more physical parametrization of the surgical method used for coarctation repair. The developed pipeline is demonstrated on an animal model of aortic coarctation. Future directions for extending computational geometric tools for analysis-driven virtual surgery are also motivated.

Meshless Hemodynamics Modeling and Evolutionary Shape Optimization of Bypass Grafts Anastomoses

Meshless Hemodynamics Modeling and Evolutionary Shape Optimization of Bypass Grafts Anastomoses
Author : Zaher El Zahab
Publisher : Unknown
Release Date : 2008
Category : Fluid dynamics
Total pages :151
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Objectives: The main objective of the current dissertation is to establish a formal shape optimization procedure for a given bypass grafts end-to-side distal anastomosis (ETSDA). The motivation behind this dissertation is that most of the previous ETSDA shape optimization research activities cited in the literature relied on direct optimization approaches that do not guaranty accurate optimization results. Three different ETSDA models are considered herein: The conventional, the Miller cuff, and the hood models. Materials and Methods: The ETSDA shape optimization is driven by three computational objects: a localized collocation meshless method (LCMM) solver, an automated geometry pre-processor, and a genetic-algorithm-based optimizer. The usage of the LCMM solver is very convenient to set an autonomous optimization mechanism for the ETSDA models. The task of the automated pre-processor is to randomly distribute solution points in the ETSDA geometries. The task of the optimized is the adjust the ETSDA geometries based on mitigation of the abnormal hemodynamics parameters. Results: The results reported in this dissertation entail the stabilization and validation of the LCMM solver in addition to the shape optimization of the considered ETSDA models. The LCMM stabilization results consists validating a custom-designed upwinding scheme on different one-dimensional and two-dimensional test cases. The LCMM validation is done for incompressible steady and unsteady flow applications in the ETSDA models. The ETSDA shape optimization include single-objective optimization results in steady flow situations and bi-objective optimization results in pulsatile flow situations. Conclusions: The LCMM solver provides verifiably accurate resolution of hemodynamics and is demonstrated to be third order accurate in a comparison to a benchmark analytical solution of the Navier-Stokes. The genetic-algorithm-based shape optimization approach proved to be very effective for the conventional and Miller cuff ETSDA models. The shape optimization results for those two models definitely suggest that the graft caliber should be maximized whereas the anastomotic angle and the cuff height (in the Miller cuff model) should be chosen following a compromise between the wall shear stress spatial and temporal gradients. The shape optimization of the hood ETSDA model did not prove to be advantageous, however it could be meaningful with the inclusion of the suture line cut length as an optimization parameter.

Dissertation Abstracts International

Dissertation Abstracts International
Author : Anonim
Publisher : Unknown
Release Date : 2008
Category : Dissertations, Academic
Total pages :129
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