The effect of the dietary macronutrient composition on weight loss has been a controversial issue for decades. During that time, a high-protein, high-fat, and low-carbohydrate diet has been one of the more popular weight loss diets with the public. We hypothesized that a computer simulation model using STELLA software could help to better understanding the effect of the dietary macronutrient composition on weight loss. We calculated daily total oxidation instead of total energy expenditure as others have done based on the facts that carbohydrate, fat, and protein intake influence carbohydrate, fat, and protein oxidation. In order to create a simple and accurate model comparing dietary macronutrient composition effects, we eliminated exercise as a factor and focused on a sedentary population. The model was validated by five sets of published human data. Following model validation, simulations were carried out to compare the traditional high-carbohydrate diet recommended by the American Dietetic Association and two well-known high-protein diets (Atkins and the Zone diet). The results of computer simulation suggested that the lean tissue retention effect of a high-protein diet, especially with a lower-fat diet, compared with a traditional high carbohydrate diet over 6 months.

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A reversible solid oxide fuel cell (RSOFC) system could buffer intermittent electrical generation, e.g. wind, wave power by storing electrical energy as hydrogen and heat. RSOFC were fabricated by thermoplastic extrusion of (La₀.₈Sr₀.₂)₀.₉₅MnO[subscript(3−δ)] (LSM) ceramic support tubes, which were microstructurally stable with 55% porosity at 1350°C. A composite oxygen electrode of LSM-YSZ was applied, providing a homogeneous substrate for a 20 μm - 30 μm thick YSZ electrolyte. A dip-coated 8YSZ slurry, and a painted commercial 3YSZ ink gave sintered densities of 90% and nearly 100% at 1350°C, respectively. A porous NiO/YSZ fuel electrode was also painted on. A Ag/Cu reactive air braze was unsuccessful at forming a void-free joint between the RSOFC and a 316 stainless steel gas delivery tube, as the braze did not penetrate the oxidation layer on the steel. Two alumina-based ceramic cements failed to fully seal the cell to an alumina gas delivery tube, due to thermal expansion coefficient mismatches and porosity after curing. Therefore, the maximum open circuit voltage (OCV) obtained during RSOFC testing was 0.8 V at 440°C. LSM-YSZ symmetrical cell performance measurements with oxygen pressure showed a diffusion polarisation, which was assigned to dissociative adsorption and surface diffusion of oxygen species. A collaborative RSOFC system software model showed ohmic and activation losses dominated the RSOFC, and diffusion losses were insignificant. Pressurisation from 1 to 70 bar increased the RSOFC Nernst voltage by 11% at 900°C, and reduced the entropy of the gases, reducing heat production and increasing electrical efficiency. A 500 kg Sn/Cu phase change heat store prevented the system overheating. Over a 16 h discharge-charge RSOFC cycle in the range 5 mol.% - 95 mol.% hydrogen in steam, at 20.4 A per cell or 3250 A m⁻², the electrical energy storage efficiency was 64.4%.

Baigiamajame magistro darbe atlikta daugiainduktorės elektros pavaros valdymo būdų analizė. Pateikiami tiesiaeigio asinchroninio variklio statinių charakteristikų skaičiavimai. Sudaryti daugiainduktorės elektros pavaros kompiuteriniai modeliai: fazinėje koordinačių sistemoje ir x, y koordinačių sistemoje. Tiriamojoje dalyje pateiktos daugiainduktorės elektros pavaros jėgos, pagreičio, greičio, kelio, srovės dinaminės charakteristikos, kai induktoriai maitinami iš pastovios įtampos ir dažnio elektros tinklo. Taip pat pateikiamos jėgos, pagreičio, greičio, kelio, srovės dinaminės charakteristikos, kai induktoriai maitinami iš skirtingos įtampos ir dažnio elektros tinklo. Remiantis gautais rezultatais baigiamojo darbo pabaigoje suformuluotos išvados ir pasiūlymai. Prieduose pateikiami TAV statinių charakteristikų skaičiavimo rezultatai, kompiuterinio modelio programa. Darbą sudaro 8 dalys: įvadas, literatūros apžvalga, tyrimo tikslas ir uždaviniai, teorinė dalis, tiriamoji dalis, išvados ir pasiūlymai, literatūra ir kiti šaltiniai, priedai. Darbo apimtis – 64 p. teksto be priedų, 65 iliustr., 2 lentelės 33 bibliografiniai šaltiniai. / In the Final Master Thesis analyzed control methods of multi inductor linear electric drive . Provided the linear induction motor operating characteristics calculations. Moreover, two types of computer models are created: in phase coordinate system and x, y coordinate system. At the research part presented multi inductor electric drive force, acceleration, speed, road, current dynamic characteristics, when inductors are powered by a constant voltage and frequency of the mains. Also presents force, acceleration, speed, road, current dynamic characteristics, when inductors are powered from different voltage and frequency of the mains. Based on the results of the thesis provides conclusions and recommendations. At the annexes part presented calculation results of linear electric motor static characteristics and application of a computer model. The Thesis consists of 8 sections: introduction, literature review, research purpose and objectives, the theoretical part, research part, conclusions and suggestions, references and other sources and annexes. The Thesis includes: 64 pages of the text without annexes, 65 figures, 2 tables, 33 references.

La compréhension clinique et le traitement des maladies cardiovasculaires est extrêmement complexe. Pour chaque patient, les cardiologues sont confrontés à des difficultés pour déterminer la pathologie, choisir une thérapie ou encore sélectionner les patients susceptibles de bien répondre à un traitement donné. Afin de fournir une aide additionnelle aux cardiologues, de nombreuses équipes de recherche étudient la possibilité de planifier de telles thérapies grâce à des modèles biophysiques du cœur. Ils formulent l'hypothèse que l'on peut combiner les données fonctionnelles et anatomiques afin de créer des modèles cardiaques personnalisés à chaque patient qui auraient le potentiel de prédire les bénéfices des différentes thérapies. Les simulations électromécaniques du cœur sont basées sur des modèles informatiques qui peuvent représenter la géométrie, le mouvement et la propagation d'ondes électriques pendant un cycle cardiaque avec suffisamment de précision. L'intégration d'information anatomique, mécanique et électrophysiologique pour un patient donné est essentielle pour construire ce type de modèle.Dans cette thèse, nous présentons tout d'abord les méthodes de personnalisations géométriques, cinématiques et électrophysiologiques nécessaires à toutes modélisations mécaniques. Nous utilisons ensuite le modèle électromécanique de Bestel-Clément-Sorine qui a déjà prouvé avoir un bon réalisme sans être trop complexe au vu des données disponibles. Nous commençons par détailler la nouvelle implémentation de ce modèle dans une plateforme efficace de simulation médicale ayant l'avantage d'être libre et interactive, puis nous analysons les résultats de la simulation par une étude de sensibilité complète.Dans un deuxième temps, nous étudions la possibilité de personnaliser les paramètres mécaniques de ce modèle à partir d'images médicales (IRM). Pour cela, nous proposons en premier lieu une méthode automatique de calibration qui estime les paramètres mécaniques globaux à partir de courbes de pressions et volumes. Cette technique testée sur 6 volontaires et 2 cas pathologiques nous a permis de faire une étude de spécificité qui consiste à déterminer les paramètres pertinents capables de différencier les cas pathologiques des cas sains.Une fois initialisés à ces valeurs calibrées, les paramètres sont personnalisés localement avec un algorithme d'optimisation plus complexe. Le « Reduced Order Unscented Kalman Filtering » est utilisé pour estimer les contractilités de toutes les zones AHA du ventricule gauche à partir des volumes régionaux extraits des séquences d'images IRM. Cette stratégie de personnalisation a été validée et testée sur plusieurs cas pathologiques et volontaires. Ces différentes contributions ont montré des résultats prometteurs tout au long de cette thèse et certains sont déjà utilisés pour quelques études de recherche. / The clinical understanding and treatment of cardiovascular diseases is highly complex. For each patient, cardiologists face issues in determining the pathology, choosing a therapy or selecting suitable patients for the therapy. In order to provide additional guidance to cardiologists, many research groups are investigating the possibility to plan such therapies based on biophysical models of the heart. The hypothesis is that one may combine anatomical and functional data to build patient-specific cardiac models that could have the potential to predict the benefits of different therapies. Cardiac electromechanical simulations are based on computational models that can represent the heart geometry, motion and electrophysiology patterns during a cardiac cycle with sufficient accuracy. Integration of anatomical, mechanical and electrophysiological information for a given subject is essential to build such models.In this thesis, we first introduce the geometry, kinematics and electrophysiology personalizations that are necessary inputs to mechanical modeling. We propose to use the Bestel-Cl'ement-Sorine electromechanical model of the heart, which is sufficiently accurate without being over-parametrized for the available data. We start by presenting a new implementation of this model in an efficient opensource framework for interactive medical simulation and we analyze the resulting simulations through a complete sensitivity analysis.In a second step, the goal is to personalize the mechanical parameters from medical images (MRI data). To this end, we first propose an automatic calibration algorithm that estimates global mechanical parameters from volume and pressure curves. This technique was tested on 7 volunteers and 2 heart failure cases and allowed to perform a preliminary specificity study that intends to determine the relevant parameters able to differentiate the pathological cases from the control cases.Once initialized with the calibrated values, the parameters are then locally personalized with a more complex optimization algorithm. Reduced Order Unscented Kalman Filtering is used to estimate the contractilities on all of the AHA zones of the Left Ventricle, matching the regional volumes extracted from cine MRI data. This personalization strategy was validated and tested on several pathological and healthy cases. These contributions have led to promising results through this thesis and some are already used for various research studies.

An innovative mathematical architecture for modelling neuronal electrical activity is presented, called the cognitive rhythm generator (CRG), wherein the proposed architecture is a hybrid model comprised of three interconnected stages, namely: (1) a bank of neuronal modes; (2) a ring device (limit-cycle oscillator); and (3) a static output nonlinearity (mapper). Coupled CRG networks are employed to emulate and elucidate the dynamics of biological neural networks, including the recurrent networks in the hippocampus. Several species of ring devices are described and investigated, including the clock, labile clock, hourglass and multistable ring systems, and their applications to neuronal modelling explored. Complexity measures such as the maximum Lyapunov exponent, correlation dimension and detrended fluctuation analysis are applied to compare model and biological records and validate the CRG methodology. The basis of neural coding is also examined in mathematical detail, with particular regard to its description by Volterra-Wiener kernel formalism, from which the neuronal modes are derived. Applications to theta-gamma coding are discussed. Further on in the thesis, a CRG epileptiform network model of spontaneous seizure-like events (SLEs) is developed and used as a platform to test neuromodulation approaches for seizure abatement. (Neuromodulation mentioned here refers to methods involving electrical stimulation of neural tissue for therapeutic benefit). Spontaneous SLE transitions in the epileptiform network are shown to be related to the mechanism of intermittency, as determined by examining the state space dynamics of the model. The onset of SLEs is associated with increased network excitability and decreased stability, consistent with experimental results from the low-magnesium/high-potassium in vitro model of epilepsy. Lastly, a novel strategy for therapeutic neuromodulation is presented wherein a coupled CRG network (called the “therapeutic network”) is interfaced with the epileptiform network model, forming a closed loop for responsive, biomimetic neuromodulation of the epileptiform network. Relevance to clinical applications and future work is discussed.

An innovative mathematical architecture for modelling neuronal electrical activity is presented, called the cognitive rhythm generator (CRG), wherein the proposed architecture is a hybrid model comprised of three interconnected stages, namely: (1) a bank of neuronal modes; (2) a ring device (limit-cycle oscillator); and (3) a static output nonlinearity (mapper). Coupled CRG networks are employed to emulate and elucidate the dynamics of biological neural networks, including the recurrent networks in the hippocampus. Several species of ring devices are described and investigated, including the clock, labile clock, hourglass and multistable ring systems, and their applications to neuronal modelling explored. Complexity measures such as the maximum Lyapunov exponent, correlation dimension and detrended fluctuation analysis are applied to compare model and biological records and validate the CRG methodology. The basis of neural coding is also examined in mathematical detail, with particular regard to its description by Volterra-Wiener kernel formalism, from which the neuronal modes are derived. Applications to theta-gamma coding are discussed. Further on in the thesis, a CRG epileptiform network model of spontaneous seizure-like events (SLEs) is developed and used as a platform to test neuromodulation approaches for seizure abatement. (Neuromodulation mentioned here refers to methods involving electrical stimulation of neural tissue for therapeutic benefit). Spontaneous SLE transitions in the epileptiform network are shown to be related to the mechanism of intermittency, as determined by examining the state space dynamics of the model. The onset of SLEs is associated with increased network excitability and decreased stability, consistent with experimental results from the low-magnesium/high-potassium in vitro model of epilepsy. Lastly, a novel strategy for therapeutic neuromodulation is presented wherein a coupled CRG network (called the “therapeutic network”) is interfaced with the epileptiform network model, forming a closed loop for responsive, biomimetic neuromodulation of the epileptiform network. Relevance to clinical applications and future work is discussed.

付記する学位プログラム名: グローバル生存学大学院連携プログラム / 京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第21056号 / 工博第4420号 / 新制||工||1687(附属図書館) / 京都大学大学院工学研究科社会基盤工学専攻 / (主査)教授 寶 馨, 教授 角 哲也, 准教授 佐山 敬洋 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

Transcatheter aortic heart valve replacement (TAVR) is a procedure to replace a failing aortic valve and is becoming the new standard of care for patients that are not candidates for open-heart surgery [2]. However, this minimally invasive technique has shown to cause ischemic brain lesions, or “silent infarcts”, in 90% of TAVR patients, which can increase the patient’s risk for stroke by two to four times in future years [3]. Claret Medical Inc., a medical device company, has developed a cerebral protection system that filters and captures embolic debris released during endovascular procedures, such as TAVR. This thesis utilized CT scans from Claret Medical to create a physical construct of the aortic arch to experimentally validate a theoretical computer model through flow visualization. The hypothesis was that the empirical model can accurately mimic the fluid dynamic properties of the aortic arch in order validate an in silico model using the finite elements program COMSOL MultiPhysics® Modeling Software. The physical model was created from a patient CT scan of the aortic arch using additive manufacturing (3D printing) and polymer casting, resulting in the shape of the aortic arch within a transparent, silicone material. Fluid was pumped through the model to visualize and quantify the velocity of the fluid within the aortic arch. COMSOL MultiPhysics® was used to model the aortic arch and obtain velocity measurements, which were statistically compared to the velocity measurements from the physical model. There was no significant difference between the values of the physical model and the computer model, confirming the hypothesis. Overall, this study successfully used CT scans to create an anatomically accurate physical model that was validated by a computer model using a novel technique of flow visualization. As TAVR and similar procedures continue to develop, the need for experimental evaluation and visualization of devices will continue to grow, making this project relevant to many companies in the medical device industry.

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