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Quantitative Structure Activity Relationship (QSAR) is a very useful computa-tional method which has facilitated great progress in drug development [1]. Thismethod can be used to predict a molecule’s activity against a certain target justby comparing its structural characteristics (i.e., molecular descriptors) with thosebelonging to molecules of known activity. QSAR modeling is fueled by online freedatabases consisting of millions of active and inactive molecules and by MachineLearning (ML) Methods that enable data analysis. To ensure successful implemen-tation of ML models, there is a range of evaluation methods to estimate their perfor-mance and applicability domain. So far, a great deal of research has focused on theuse of Support Vector Machines (SVMs) to classify molecules with the use of theirMolecular Signature Fingerprints as descriptors [2]. However, another MachineLearning algorithm, Deep Neural Networks (DNNs), an improvement of single-layer Neural Networks, is rising in popularity in various fields including moleculeclassification. The two models were compared using CPSign software which intro-duces Conformal Prediction, to evaluate the reliability of model predictions basedon performance for individual compounds rather than mean performance on agiven test set. Three types of descriptors were used: Molecular Signature Finger-prints, Extended Connectivity Fingerprints and physicochemical descriptors. Thecomparison showed that Multilayer Perceptron (MLP) which was used as a DNNrepresentative in current context, had performance similar to the shallower SVMmodels but additionally demanded longer training times [3]. It can be concludedthat in the field of QSAR with the aforementioned descriptors, when the numberof examples used for training is not immense, Support Vector Machines might per-form equally well and demand less resources and time than the more sophisticated MLPs.

Additive manufacturing (AM) has received much attention from researchers over the past decades because of its diverse applications in various industries. AM is an advanced manufacturing process that facilitates the fabrication of complex geometries represented by computer-aided design (CAD) models. Traditionally, designed parts are fabricated by extruding material layer-by-layer using a tool path planning obtained from slicing programs by using CAD models as an input. Recently, there has been a growing interest in non-planar AM technologies, which offer the ability to fabricate multilayer constructs conforming to freeform surfaces. Non-planar AM processes have been utilized in various applications and involved objects of varying material properties and geometric characteristics. Although the current state of the art suggests AM can provide novel opportunities in conformal manufacturing, several challenges remain to be addressed. The identified challenges in non-planar AM fall into three categories: 1) conformal 3D printing on substrates with complex topography of which CAD model representation is not readily available, 2) understanding the relationship between the tool path planning and the quality of the 3D-printed construct, and 3) conformal 3D printing in the presence of mechanical disturbances. An open-loop non-planar tool path planning algorithm based on point cloud representations of object geometry and a closed-loop non-planar tool path planning algorithm based on position sensing were proposed to address these limitations and enable conformal 3D printing and spatiotemporal 3D sensing on objects of near-arbitrary organic shape. Three complementary studies have been completed towards the goal of improving the conformal tool path planning capabilities in various applications including fabrication of conformal electronics, in situ bioprinting, and spatiotemporal biosensing: i. A non-planar tool path planning algorithm for conformal microextrusion 3D printing based on point cloud data representations of object geometry was presented. Also, new insights into the origin of common conformal 3D printing defects, including tool-surface contact, were provided. The impact and utility of the proposed conformal microextrusion 3D printing process was demonstrated by the fabrication of 3D spiral and Hilbert-curve loop antennas on various non-planar substrates, including wrinkled and folded Kapton films and origami. ii. A new method for closed-loop controlled 3D printing on moving substrates, objects, and unconstrained human anatomy via real-time object position sensing was proposed. Monitoring of the tool position via real-time sensing of nozzle-surface offset using 1D laser displacement sensors enabled conformal 3D printing on moving substrates and objects. The proposed control strategy was demonstrated by microextrusion 3D printing on oscillating substrates and in situ bioprinting on an unconstrained human hand. iii. A reverse engineering-driven collision-free path planning program for automated inspection of macroscale biological specimens, such as tissue-based products and organs, was proposed. The path planning program for impedance-based spatiotemporal biosensing was demonstrated by the characterization of meat and fruit tissues using two impedimetric sensors: a cantilever sensor and a multifunctional fiber sensor. / Doctor of Philosophy / Additive Manufacturing (AM), commonly referred to as 3D printing, is a computer-aided manufacturing process that facilitates the fabrication of personalized and customized models, tissues, devices, and wearables. AM has several advantages over traditional manufacturing processes. For example, directing computer-driven robotics enables control over spatial structure and composition of parts. While 3D printing is typically performed using layer-by-layer planar tool paths generated by slicing programs, non-planar 3D printing is an emerging area that has recently been examined for various post-processing applications. Processes that enable material deposition conforming to complex geometric and freeform objects (e.g., anatomical structures), are central to various industries, including additive manufacturing, electronics manufacturing, and biomanufacturing. In this dissertation, tool path planning methods and real-time control strategies for non-planar 3D printing onto stationary and moving arbitrary surfaces, and various conformal electronics and in situ bioprinting applications will be presented. In addition to the tool path planning methods for 3D printing, a collision-free path planning program will be proposed for the inspection of large tissues and organs. The utility of the proposed method will be demonstrated through electrical impedance-based biosensing of meat and fruit to characterize their compositional and physiochemical properties which are used for quality assessment.

Non-planar additive manufacturing (AM) technologies, such as microextrusion 3D printing processes, offer the ability to fabricate conformal electronics with impressive structure and function on curvilinear substrates. Although various available methods offer conformal 3D printing capability on objects with limited geometric complexity, a number of challenges remain to improve feature resolution, throughput, materials compatibility, resultant function and properties of printed components, and application to substrates of varying topography. Hence, the overall objective of this dissertation was to create new non-planar AM processes that are compatible with personalized and anatomical computer-aided design workflows for the fabrication of conformal electronics and form-fitting wearables. After reviewing the current state of knowledge and state of the art, significant challenges in non-planar AM have been identified as: 1) limited non-planar AM path planning capability that synergizes with personalized or anatomical object surface modification, 2) limited approaches for printed and non-printed component integration on non-planar substrates. To address these challenges, a template-based reverse engineering workflow is proposed for conformal 3D printing electronics and form-fitting wearable devices on anatomical structures. This work was organized into three complementary tasks that enhance non-planar AM capabilities: 1） To achieve anatomical tissue-sensor integration, 3D scanning-based point cloud data acquisition and customized 3D printable conductive ink are proposed for capturing the topographical information of patient-specific malformations and integrating conformal sensing electronics across anatomical tissue-device interface. 2） To fabricate conformal antennas on flexible thin-film polymer substrates, a versatile method for microextrusion 3D printing of conformal antennas on thin film-based structures of random topography is proposed to control the ink deposition process across the curvilinear surfaces of freeform Kapton-based origami. 3） To simplify the fabrication process of form-fitting wearable devices with fiber-based form factors and self-powered capability, an innovative 3D printing process is proposed to achieve coaxial multi-material extrusion of metal-elastomer triboelectric fibers. By developing new advanced non-planar printing processes and conformal toolpath programming strategies, the utility of non-planar AM could be further expanded for fabricating various personalized implantable and wearable multi-functional systems, including novel 3D electronics. In summary, this work advances capability in additive manufacturing processes by providing new advances in multi-material extrusion processes and personalized device design and manufacturing workflows. / Doctor of Philosophy / The ability to assemble electronic devices on three-dimensional objects with complex geometry is essential for developing next-generation wearable devices. Additive manufacturing processes, commonly referred to as 3D printing, now offer the ability to fabricate conformal electronics on surfaces and objects with non-planar geometry. This dissertation aims to expand non-planar 3D printing capabilities for applications to objects with anatomical or personalized structures, such as patient-specific malformation and origami. The proposed methods in this dissertation are focused on addressing challenges, such as the acquisition of object 3D topographical data, material selection, and tool path programming for objects that exhibit anatomical geometry. The utility of the proposed methods is demonstrated with practical applications to 3D-printed conformal electronics and wearable devices for monitoring human behavior and organ healthcare. This dissertation contributes to improving manufacturing capability and outcomes of 3D-printed form-fitting wearable and implantable devices. Future work may emphasize developing biocompatible functional ink and toolpath programming algorithms with real-time adaptation capability.

The overall goal of this research work is to enhance the capabilities of large-format, polymer material extrusion, additive manufacturing (AM) systems. Specifically, the aims of this research are to (1) Construct, and develop a robust workflow for, a large-format, robotic, AM system; (2) Develop an algorithm for determining and relaying proper rotation commands for 5 degree of freedom (DoF) multi-axis deposition; and (3) Create a method for printing a removable support material in large-format AM. The development and systems-integration of a large-format, pellet-fed, polymer, material extrusion (ME), AM system that leverages an industrial robotic arm is presented. The robotic arm is used instead of the conventional gantry motion stage due to its multi-axis printing ability, ease of tool changes for multi-material deposition and/or subtraction, and relatively small machine footprint. A novel workflow is presented as a method to control the robotic arm for layer-wise fabrication of parts, and several machine modifications and workflow enhancements are presented to extend the multi-axis manufacturing capabilities of the robot. This workflow utilizes existing AM slicers to simplify the motion path planning for the robotic arm, as well as allowing the workflow to not be restricted to a single robotic deposition system. To enable multi-axis deposition, a method for generating tool orientations and resulting deposition toolpaths from a geometry's STL file was developed for 5-DoF conformal printing and validated via simulation using several different multi-DOF robotic arm platforms. Furthermore, this research proposes a novel method of depositing a secondary sacrificial support material was created for large-format AM to enable the fabrication of complex geometries with overhanging features. This method employs a simple tool change to deposit a secondary, water-soluble polymer at the interfaces between the part and supporting structures. In addition, a means to separate support material into smaller sections to extend the range of geometries able to be manufactured via large-format AM is presented. The resultant method was used to manufacture a geometry that would traditionally be considered unprintable on conventional large-format AM systems. / Master of Science / Additive manufacturing (AM), also known as 3D printing, is a method of manufacturing objects in a layer-by-layer technique. Large-format AM is typically defined as an AM system that can create an object larger than 1 m3. There are only a few manufacturers in the world of these systems, and all currently are built on gantry-based motion stages that only allow movement of the printer in three principal axes (X, Y, Z). The primary goal of this thesis is to construct a large-format AM system that uses a robotic arm to enable printing in any direction or orientation. The use of an industrial robotic arm enables printing in multiple planes, which can be used to print structures without support structures, print onto curved surfaces, and to purt with curved layers which produces a smoother external part surface. The design of the large-format AM system was validated through successful printing of objects as large as 1.0x0.5x1.2 m, simultaneous printing of a sacrificial support material to enable overhanging features, and through completing multi-axis printing. To enable multi-axis printing, an algorithm was developed to determine the proper toolpath location and relative orientation to the part surface. Using a part's STL file as input, the algorithm identifies the normal vector at each movement command, which is then used to calculate the required tool orientation. The tool orientations are then assembled with the movement commands to complete the multi-axis toolpath for the robot to perform. Finally, this research presents a method of using a second printing tool to deposit a secondary, water-soluble material to act as supporting structures for overhanging and bridging part features. While typical 3D printers can generally print sacrificial material for supporting overhangs, large-format printers produce layers up to 25 mm wide, rendering any support material impossible to remove without post-process machining. This limits the range of geometries able to be printed to just those with no steep overhangs, or those where the support material is easily reachable by a tool for removal. The solution presented in this work enables the large scale AM processes to create complex geometries.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

L'objet d'étude de cette thèse est une mesure infinie sur les boucles (lacets) naturellement associée à une large classe de processus de Markov et les processus ponctuels de Poisson d'intensité proportionnelle à cette mesure (paramètre d'intensité alpha>0). Ces processus ponctuels de Poisson portent le nom d'ensembles poissoniens de boucles markoviennes ou de soupes de boucles. La mesure sur les boucles est covariante par un certain nombre de transformations sur les processus de Markov, par exemple le changement de temps.Dans le cadre de soupe de boucles brownienne à l'intérieur d'un sous-domaine ouvert propre simplement connexe de C, il a été montré que les contours extérieurs des amas extérieurs de boucles sont, pour alpha<=1/2, des Conformal Loop Ensembles CLE(kappa), kappa dans (8/3,4]. D'autre part il a été montré pour une large classe de processus de Markov symétriques que lorsque alpha=1/2, le champ d'occupation d'une soupe de boucle (somme des temps passés par les boucles aux dessus des points) est le carré du champ libre gaussien. J'ai étudié d'abord les soupes de boucles associés aux processus de diffusion unidimensionnels, notamment leur champ d'occupation dont les zéros délimitent dans ce cas les amas de boucles. Puis j'ai étudié les soupes de boucles sur graphe discret ainsi que sur graphe métrique (arêtes remplacés par des fils continus). Sur graphe métrique on a d'une part une géométrie non triviale pour les boucles et d'autre part on a comme dans le cas unidimensionnel continu la propriété que les zéros du champ d'occupation délimitent les amas des boucles. En combinant les graphes métriques et l'isomorphisme avec le champ libre gaussien j'ai montré que alpha=1/2 est le paramètre d'intensité critique pour la percolation par soupe de boucles de marche aléatoire sur le demi plan discret Z*N (existence ou non d'un amas infini) et que pour alpha<=1/2 la limite d'échelle des contours extérieurs des amas extérieurs sur Z*N est un CLE(kappa) dans le demi-plan continu. / In this thesis I study an infinite measure on loops naturally associated to a wide range of Markovian processes and the Poisson point processes of intensity proportional to this measure (intensity parameter alpha>0). This Poissson point processes are called Poisson ensembles of Markov loops or loop soups. The measure on loops is covariant with some transformation on Markovian processes, for instance the change of time. In the setting of Brownian loop soups inside a proper open simply connected domain of C it was shown that the outer boundaries of outermost clusters of loops are, for alpha1/2, Conformal Loop Ensembles CLE(kappa), kappa in (8/3,4]. Besides, it was shown for a wide range of symmetric Markovian processes that for alpha=1/2 the occupation field of a loop soup (the sum of times spent by loops over points) is the square of the Gaussian free field. First I studied the loop soups associated to one-dimensional diffusions, and particularly the occupation field and its zeroes that delimit in this case the clusters of loops. Then I studied the loop soups on discrete graphs and metric graphs (edges replaced by continuous lines). On a metric graph on one hand the loops have a non-trivial geometry and on the other hand one has the same property as in the setting of one-dimensional diffusions that the zeroes of the occupation field delimit the clusters of loops. By combing metric graphs and the isomorphism with the Gaussian free field I have shown that alpha=1/2 is the critical parameter for random walk loop soup percolation on the discrete half-plane Z*N (existence or not of an infinite cluster of loops) and that for alpha<= 1/2 the scaling limit of outer boundaries of outermost clusters on Z*N is a CLE(kappa) on the continuum half plane.

INTRODUÇÃO: Na Radioterapia, a acurácia da distribuição de dose em cálculos com correção de heterogeneidade está diretamente relacionada à escolha do algoritmo de cálculo. Existe uma variedade de algoritmos de cálculo disponíveis no mercado, variando em tempo de processamento e acurácia. Este estudo teve como objetivos quantificar a acurácia de dez diferentes algoritmos de cálculo em objetos simuladores de pulmão e analisar o impacto da escolha do algoritmo na distribuição de dose em radioterapia aplicada a tumores de pulmão. METODOLOGIA: Foram utilizados placas simuladoras de água (água sólida RW3) e pulmão (cortiça) para determinar a Porcentagem de Dose em Profundidade (PDP) e perfil transversal dentro da heterogeneidade (cortiça). As medidas foram realizadas em um Clinac Varian 6EX, com feixes de fótons de 6 MV e dois tamanhos de campo (5 x 5 cm2 e 10 x 10 cm2), irradiando-se filmes radiocrômicos Gafchromic EBT3 e câmara de ionização Scanditronix Wellhofer CC13. Planejamentos de 25 pacientes - 11 com técnica tridimendional (3D) e 14 com técnica de Radioterapia Estereotática Corpórea (SBRT) - foram realizados, inicialmente sem correção de heterogeneidade e, mantendo-se as UM, os cálculos com os diferentes algoritmos/métodos de correção foram comparados com o planejamento inicial. Foram avaliados as doses no volume alvo e nos órgãos em risco. RESULTADOS: As medidas realizadas em objetos simuladores revelaram que os algoritmos baseados no princípio da convolução (Eclipse® Pencil Beam Convolution com métodos de correção Batho, Batho Modificado e TAR equivalente; XiO® Clarkson e Convolution e iPlan® Pencil Beam) apresentaram diferenças de dose significativas na região da cortiça, sempre superestimando a medida, com uma sobredose superior a 8%. Algoritmos mais avançados, como o Eclipse® AAA e Acuros XB, XiO® Superposition e iPlan® XVMC, apresentaram desvios inferiores a 3% na região da heterogeneidade. A análise dos perfis mostra, igualmente, que a segunda classe de algoritmos apresenta melhor comportamento em meios de baixa densidade como a cortiça. A largura da penumbra apresentou desvios inferiores a 1 mm para os algoritmos mais avançados contra diferenças de até 4,5 mm entre os algoritmos baseados em convolução. A análise da distribuição de dose em planejamentos de tumores pulmonares mostrou que todos os cálculos com correção de heterogeneidade presentam doses superiores ao cálculo sem correção de heterogeneidade. O histograma dose-volume (DVH) do volume alvo sofreu um impacto maior do que dos órgãos em risco. Os cálculos realizados com algoritmos baseados em convolução apresentaram distribuições de dose semelhantes entre si, porém diferentes das do cálculo sem correção de heterogeneidade. Eclipse® AAA, Acuros XB, XiO® Superposition e iPlan® XVMC apresentaram distribuições de dose também semelhantes, porém Eclipse® Acuros XB e iPlan® XVMC são ainda mais similares. Os planejamentos de SBRT apresentaram resultados mais discrepantes do cálculo sem correção de heterogeneidade do que os planejamentos 3D. CONCLUSÕES: Os diferentes algoritmos de cálculo disponíveis possuem acurácias diferentes em meios de baixa densidade eletrônica. Essas diferenças possuem impacto nas distribuições de dose em planejamentos de tratamento de tumores pulmonares, sendo o impacto ainda maior para a técnica de SBRT. Entre os algoritmos avaliados, há pelo menos um de cada fabricante que apresentou bom desempenho em objetos simuladores de pulmão e que devem ser priorizados para o cálculo em planejamentos de tratamentos de câncer de pulmão / INTRODUCTION: In Radiotherapy, the dose distribution accuracy in heterogeneity correction calculations is directly related to the choice of calculation algorithm. There are many calculation algorithms commercially available. They vary in accuracy and processing time. This study aimed to quantify the accuracy of ten different calculation algorithms in lung equivalent material and to analyze the impact of the algorithm choice in the dose distribution in Radiotherapy applied to lung tumors. METHODS: It was used plates of water (solid water RW3) and lung (cork) equivalent materials to determine the Percentage of Depth Dose (PDD) and transversal profile inside the heterogeneity (cork). The measurements were performed in a Clinac Varian 6EX, with 6 MV photon beams and two field sizes (5 x 5 cm2 and 10 x 10 cm2), through irradiation of radiochromic films Gafchromic EBT3 and ionization chamber Scanditronix Wellhofer CC13. Treatment planning of 25 patients - 11 with tridimensional (3D) technique and 14 with Stereotactic Body Radiation Therapy (SBRT) technique - were performed, first without heterogeneity correction and, by keeping the Monitor Units (MU), the calculations were then performed with the different algorithms/methods of heterogeneity corrections and the results were compared with the initial planning. It was analyzed the target volume and organs at risk doses. RESULTS: The measurements performed in phantoms revealed that algorithms based on the convolution principle (Eclipse® Pencil Beam Convolution with correction methods Batho, Batho Modified and Equivalent TAR; XiO® Clarkson and Convolution e iPlan® Pencil Beam) presented significant dose differences in the cork region, overestimating the measurement, with a overdose higher than 8%. More advanced algorithms, as Eclipse® AAA and Acuros XB, XiO® Superposition and iPlan® XVMC, presented deviations below to 3% in the heterogeneity region. The profile analysis showed, similarly, that the second class of algorithms presents better performance in medium with low electronic density, like cork. The penumbra width presented deviations below to 1 mm for the more sophisticated algorithms against differences up to 4.5 mm between the convolution based algorithms. The dose distribution analysis in lung treatment planning showed that all the calculations performed with heterogeneity corrections presented doses higher than the calculation without heterogeneity corrections. The target volume dose-volume histogram (DVH) had a higher impact compared to the organs at risk. The calculation performed with convolution based algorithms presented dose distributions comparable, although different from the calculation performed without heterogeneity correction. Eclipse® AAA, Acuros XB, XiO® Superposition and iPlan® XVMC presented dose distribution similar, however Eclipse® Acuros XB and iPlan® XVMC are still more similar. The SBRT treatment planning presented higher deviations from the calculation with no heterogeneity correction, compared with the 3D treatment planning. CONCLUSIONS: The different calculation algorithms available have different accuracies in low density mediums. These differences have impact in the dose distributions in lung treatment planning, being the impact higher for the SBRT technique. Between the evaluated algorithms there is, at least one of each manufacturer, that presented acceptable performance in lung equivalent material and it should be the choice in lung treatment planning calculation

Konforme Potenzen des Dirac Operators einer semi Riemannschen Spin-Mannigfaltigkeit werden untersucht. Wir präsentieren einen neuen Beweis, basierend auf dem Traktor Kalkül, für die Existenz von konformen ungeraden Potenzen des Dirac Operators auf semi Riemannschen Spin-Mannigfaltigkeiten. Desweiteren konstruieren wir eine neue Familie von konform kovarianten linearen Differentialoperatoren auf dem standard spin Traktor Bündel. Weiterhin verallgemeinern wir den Existenzbeweis für konforme ungerade Potenzen des Dirac Operators auf semi Riemannsche Spin-Mannigfaltigkeiten. Da die Existenzbeweise konstruktive sind, erhalten wir explizite Formeln für die konforme dritte und fünfte Potenz des Dirac Operators. Basierend auf den expliziten Formeln zeigen wir, dass die konforme dritte und fünfte Potenz des Dirac Operators formal selbstadjungiert (anti selbstadjungiert) bezüglich des L2-Skalarproduktes auf dem Spinorbündel ist. Abschliessend präsentieren wir neue Strukturen der konformen ersten, dritten und fünften Potenz des Dirac Operators: Es existieren lineare Differentialoperatoren auf dem Spinorbündel der Ordnung kleiner gleich eins, so dass die konforme erste, dritte und fünfte Potenz des Dirac Operators ein Polynom in jenen Operatoren ist. / Conformal powers of the Dirac operator on semi Riemannian spin manifolds are investigated. We give a new proof of the existence of conformal odd powers of the Dirac operator on semi Riemannian spin manifolds using the tractor machinery. We will also present a new family of conformally covariant linear differential operators on the standard spin tractor bundle. Furthermore, we generalize the known existence proof of conformal power of the Dirac operator on Riemannian spin manifolds to semi Riemannian spin manifolds. Both proofs concering the existence of conformal odd powers of the Dirac operator are constructive, hence we also derive an explicit formula for a conformal third- and fifth power of the Dirac operator. Due to explicit formulas, we show that the conformal third- and fifth power of the Dirac operator is formally self-adjoint (anti self-adjoint), with respect to the L2-scalar product on the spinor bundle. Finally, we present a new structure of the conformal first-, third- and fifth power of the Dirac operator: There exist linear differential operators on the spinor bundle of order less or equal one, such that the conformal first-, third- and fifth power of the Dirac operator is a polynomial in these operators.