Parkinson’s Disease (PD) is a neurodegenerative disorder, within this categoryof diseases it is among the most prevalent worldwide. The etiology of PD isbased in progressive deterioration of neural tissue in the basal ganglia (neuronalnuclei located at the base of the cerebrum) and their related structures. Current research is focusing on treatment approaches to either enhance or replaceexisting pharmaceutical treatment approaches, such as dopamine replacementtherapy. In this project, the focus was on finding correlates between movementdata and neurological signals to provide insight into potential biomarkers forcomplex motor symptoms of PD. This will in turn provide a starting point forspecifically targeted closed-loop neural stimulation that alleviates these symptoms. Although the data available at the time of this thesis did not providesufficient insight to derive a conclusion on the neural correlates, a pipeline wasdeveloped, which analyzes and synchronizes kinematic and neural data and willenable further exploration as additional data is obtained.

<p dir="ltr">Introduces a new framework and state-of-the-art algorithm in closed-loop prediction for motion planning under differential constraints. More specifically, this work introduces the idea of sampling on specific "sampling regions" rather than the entire workspace to speed-up the motion planning process by orders of magnitude.</p>

According to data provided by the U.S. Department of Health and Human Services, the waiting list of organ transplantation as of April 2021 is approximately 107,550 out of which 90,908 patients are waiting for a kidney and 11,871 are waiting for a liver. In 2020, only 39,000 transplants were performed. A promising potential solution to this organ shortage crisis is rapid development of drugs for end-stage kidney and liver failure and the fabrication of organs using additive biomanufacturing (Bio-AM) processes. While progress toward industrial-scale production of 3D-bioprinted tissue models and organs remains hindered by various biological and tissue engineering challenges, such as vascularization and innervation, quality Bio-AM is impeded by lack of integrated process monitoring and control strategies. This dissertation aims to address the compelling need to incorporate sensing and control with Bio-AM processes, which are currently open-loop processes and improve the scalability and reliability of additively biomanufactured products. The specific aim is to develop a closed loop-controlled additive biomanufacturing process capable of fabricating 3D-bioprinted biological constructs (mini-tissues) of controlled mechanical properties. The proposed methodology is based on the use of embedded sensors and real-time material property sensing for feedback control of the bioprinted constructs mechanical property. There are three objectives of this dissertation: (1) experimenting and modeling the processes to understand the causal effect of process-material interactions on Bio-AM defects, (2) use of sensors to detect defects during printing, (3) prevention of the propagation of defects through closed-loop process control. This will help us understand the fundamentals of the bio-physical process interactions that govern the quality of printed biological tissue through empirical investigation of the sensor-based data This will also provide us with a real-time monitoring, closed-loop quality control strategy to prevent the propagation of quality defects by executing corrective actions during the whole duration of the printing process. / Doctor of Philosophy / As of April 2021, there are 107,550 patients on the national transplant list out of which approximately 39,000 patients received a transplant. Simultaneously, drug development remains an expensive and time-consuming endeavor. These burden on the public and healthcare system are expected to further increase compounded by the rapidly aging population in the United States with 80 million people expected to be older than 65 years old by 2040. Additive biomanufacturing processes, commonly referred to as 3D bioprinting processes, are automated biofabrication processes that offer great potential toward manufacturing future therapeutics and models for drug discovery. Despite all the benefits and the versatility that 3D printing provides, it does not come without its own shortcomings. Additive biomanufacturing is traditionally an open-loop process, meaning the process parameters are not adjusted during the biofabrication process making it challenging to detect and correct defects during processing and achieve high reproducibility and product quality. While the dimensional characteristics and material properties are important quality signatures of a cell-based products, there are additional signatures associated with the cell quality. Some of these quality attributes include cell viability, cell proliferation, metabolic activity, morphology, and gene expression profile. Given the clinical importance and invasive nature of bio-products such as scaffolds for tissue regeneration and stem cell therapy, rigorous approaches for characterization, monitoring, and control of quality are critical to future additive bio-manufacturing paradigms. In particular, the elastic modulus of the extracellular matrix has been found to have an influence on the cell morphology, proliferation, and differentiation process. Hence, it is an excellent parameter to monitor as a measure of tissue quality. However, the traditional techniques used to characterize tissue elastic modulus are low-throughput, offline techniques and face challenges with tissue integration. Thus, there is a need for integrated sensors that can measure the modulus of tissues during 3D bioprinting. This dissertation aims to address some of these issues by developing a multi-material 3D printing and pick-and-place approach to develop smart tissue cultureware and designing a tissue integrated closed-loop feedback sensor system for polymerization of hydrogels.

Yes / The role of closed loop supply chains (CLSC) for creating and recovering value is widely acknowledged in supply chain management and there are many examples, mainly in the business-to-business sector, of successful OEM remanufacturing. The integration of value creation and recovery activities into retail customer value propositions is, however, under researched and raises many challenges, especially in Fast Moving Consumer Goods (FMCG) retail where few real world examples have been published. The recent emergence of the term ‘circular economy’ has initiated further debate about closed loop value propositions and closed loop supply chain implications. This paper selects four circular economy-led closed loop product case examples from a major European FMCG company, and assesses, at a high level, how these cases created value, for whom value was created, and key challenges in their implementation. The findings highlight that each case is different. Closing loops and creating successful value propositions is complex and requires simultaneous reconfiguration of key building blocks to ensure customer acceptance and business viability. The paper proposes the term ‘circular supply chain’ for cases where circular economy principles are explicitly incorporated in CLSC for value creation.

In laser materials processing, the direct measurement and characterization of material and process depth is traditionally a diffcult task. This is particularly difficult when such information needs to be obtained in real-time for feedback and dynamic analysis applications. This thesis outlines a novel method and apparatus for real-time depth measurement during laser processes such as welding, drilling, cutting and ablation called inline coherent imaging (ICI). The approach borrows the coherent imaging ideas from the primarily medical field of optical coherence tomography and adapts them to the new application. Without requirements for flawless image quality and limitations on sample exposure the design is free to emphasize speed in acquisition and processing. Furthermore, the imaging optics are specialized for compatibility with off-the-shelf beam delivery systems. Several generations of the imaging technique and relevant design equations are described and shown and realized. Also described is the design and construction of two laser processing stations used for testing ICI in macro- and micro-processing applications. A variety of applications for ICI in the understanding of percussion drilling and welding of metals and other industrial materials are discussed. The imaging technique is further extended to provide manual and fully automatic closed-loop control of drilling and ablation processes in industrial materials. Finally, some important applications of ICI in the processing of bone in both open and closed-loop configurations are demonstrated. / Thesis (Ph.D, Physics, Engineering Physics and Astronomy) -- Queen's University, 2012-11-20 15:31:21.708

Approved for public release, distribution is unlimited / This thesis studies the feasibility of developing a closed-loop shipboard sensor calibration system with two main objectives. The first objective was to reduce the number of personnel required to calibrate a shipboard sensor by 50%. The second was to reduce the time required to complete the calibration process by 60%. This was achieved by displaying the sensor data and the calibration standard data on a tablet PC. Wireless technology was used to transmit the data from the sensor and the calibration standard to the tablet PC. The data from the sensor is sent via IEEE 802.11b wireless LAN using DataSocket protocol and the calibration standard is sent via Bluetooth protocol. The technology can be installed and used on current ships in the United States Navy. Four software programs were developed to accomplish these goals. One program runs on the tablet PC and the other three run on the network capable application processor (NCAP). These four programs accomplish the goals stated. / Lieutenant, United States Navy

Le système MIMO coopératif est une solution attrayante dans un environnement où les trajets multiples signalent s'avérer être une étape stimulante pour le lien paire communication émetteur-récepteur. En effet, la diversité spatiale fournis par les émetteurs et recievers peut être exploitée pour améliorer la qualité du signal. Cette thèse étudie l'application de la boucle fermée précodeur MIMO pour réduire encore plus l'énergie de transmission dans un tel environnement. La contribution de cette thèse est de proposer des approches globales qui conduisent à l'optimisation globale des transmissions dans le système MIMO coopératif. Tout d'abord, on exploite la diversité spatiale des noeuds, et proposons une technique de sélection de noeud pour réduire l'énergie de transmission. Les noeuds sont sélectionnées en utilisant le linéaire boucle fermée MIMO précodeur max-dmin qui optimise la distance minimale (dmin) de critère pour réduire le BER de la constellation reçue, ce qui abaisse le rapport requis signal sur bruit (SNR). Deuxièmement, nous sommes motivés par une obligation de rendre les paramètres d'évaluation des performances MIMO disponibles aux couches supérieures du protocole. Ainsi, nous proposons une méthode théorique pour obtenir la fonction de distribution de probabilité (pdf) de dmin pour le précodeur max-dmin, nous utilisons le résultat de rapprocher le BER et de la capacité ergodique pour un système MIMO et une valeur de M en utilisant deux sous-canaux dans d'une manière rapide. Nous présentons un scénario qui exige que l'information pertinente soit détectée à partir d'une variété de sources situées à l'intérieur de la haute tension (HT) environnement du poste de réseau intelligent (SG) des applications. Notre contribution comprend le développement d'un outil de simulation basé sur la technique de sélection de noeuds pour le max-dmin distribué MIMO précodage. Pour tenir compte des interactions entre les couches multiples de communication, nous proposons de concevoir un système de communication MIMO coopératif complet basé sur un protocole d'échange de base qui est liée à notre scénario de transmission supposé. On construit en outre toutes les trames de sous-couche MAC, qui sont transmis dans ce système limité par le coût de l'énergie et de la synchronisation. / Cooperative MIMO system worked from the spatial diversity provided by the transmitters and receivers locations to improve the quality of service in the communication exchange. In our work, we explored the application of closed-loop MIMO precoder to further limit the energy of transmission in such environment. Our contribution is to propose approaches that lead to global optimization of transmissions in cooperative MIMO system. Firstly, we exploit spatial diversity of nodes, and then a node selection technique to reduce the energy of transmission. The nodes are selected using the max-dmin linear closed-loop MIMO precoder which, optimizes the minimum distance (dmin) criterion to reduce the Bit Error Rate of the received constellation, thereby lowering the required signal-to-noise ratio. Secondly, we are motivated by a requirement to make the MIMO performance evaluation parameters available to higher protocol layers. Thus, we propose a theoretical method to derive the probability distribution function of dmin for the max-dmin precoder, then we use the result to approximate the Bit Error Rate and ergodic capacity for any MIMO system and any value of modulation size M using 2 subchannels in a rapid manner. To achieve our objective, we present a realistic scenario from an existing application case where data must be collected from a variety of sources located inside a high voltage substation environment (smart grid applications). Our contribution involves the development of a simulation tool based on node selection technique for the max-dmin distributed MIMO precoding. Finally, inside this transmission scenario, we propose a complete communication system based on a basic exchange protocol. We further construct all the MAC sub layer frames that are transmitted in this system constrained by energy and synchronization cost.

INTRODUÇÃO: O desmame da ventilação mecânica é um processo complexo que requer avaliação e interpretação de parâmetros clínicos objetivos e subjetivos. O atraso no processo de desmame pode expor o paciente a um desconforto desnecessário, aumentar o risco de complicações e custos. Os modos de desmame automatizados podem acelerar a extubação e diminuir a carga de trabalho da equipe da UTI. Há diversos modos automatizados de desmame disponíveis que foram avaliados, separadamente, em populações selecionadas, com resultados divergentes em relação ao desmame convencional. No entanto, os modos automáticos desmame não foram comparados entre si, nem sistematicamente avaliados, em condições específicas, mas comuns, como a ansiedade extrema ou esforços inspiratórios inefetivos. OBJETIVOS: Comparar os modos Smartcare®, ASV® e MRV® quanto a eficácia no desmame da ventilação mecânica. MÉTODOS: Estudo de bancada para avaliar os três diferentes modos de desmame automatizado: adaptive support ventilation (ASV®), mandatory rate ventilation (MRV®) and Smartcare®. Nós simulamos os pacientes usando um simulador pulmonar programável (ASL 5000 - Ingmar Medical) com o padrão respiratório, mecânica respiratória e CO2 arterial de derivados de artigos publicados em periódicos médicos para criar duas condições: 1.extubação provável: mecânica pulmonar normal, ansiedade extrema, idosos normais, padrão de respiração irregular extrema (Cheyne-Stokes), doença pulmonar restritiva; 2. extubação improvável: mecânica pulmonar alterada, com e sem esforços inspiratórios ineficazes. RESULTADOS: Os pacientes com extubação possível, ansiedade extrema, o padrão de respiração irregular moderada e extubação impossível foram diagnosticados corretamente por todos os modos. Os pacientes com Cheyne-Stokes foram diagnosticados impropiamennte por todos os modos, mas o modo Smartcare® diagnosticou corretamente quando a opção de distúrbio neurológico foi ativado. Apenas o Smartcare® diagnosticou corretamente o paciente com respiração rápida e superficial, devido à doença pulmonar restritiva. Somente o modo MRV® diagnosticou impropriamente o paciente com esforços inspiratórios ineficazes. O nível de estabilização da pressão de suporte variou para cada modo. ASV® e MRV® atingiram nível de pressão de suporte estável mais rápido do que Smartcare®. No entanto, especialmente para ASV®, não houve estabilização da pressão de suporte, mas oscilação da pressão ao longo de um grande intervalo. CONCLUSÃO: Os três modos de desmame automatizada tiveram desempenho correto na maioria dos pacientes, mesmo em condições adversas, como a ansiedade extrema. Pacientes com respiração rápida e superficial, devido à doença pulmonar restritiva, esforços inspiratórios ineficazes e Cheyne Stokes, foram impropriamente diagnosticados, dependendo do modo. ASV® e MRV® tem respostas mais rápidas, mas apresentaram grande variação do nível da pressão de suporte, especialmente de modo a ASV® / INTRODUCTION: Weaning from mechanical ventilation is a complex process requiring assessment and interpretation of both objective and subjective clinical parameters. Delay in weaning process may expose the patient to unnecessary discomfort and increased risk of complications, and increasing the cost of care. Automated weaning modes could quicken the extubation and decrease the ICU team workload. Many automated weaning modes were now available. They were separately evaluated in selected populations with divergent results when compared to conventional weaning. However the automated weaning modes were not compared among them, neither systematically evaluated in challenging but common conditions, as extreme anxiety or ineffective inspiratory efforts. OBJECTIVES: Compare Smartcare®, ASV® and MRV® effectiveness in weaning of mechanical ventilation. METHODS: Bench study to evaluate three different automated weaning modes: adaptive support ventilation (ASV®), mandatory rate ventilation (MRV®) and Smartcare®. We simulated the patients using a programmable lung simulator (ASL 5000 Ingmar Medical) with the breathing pattern, respiratory mechanics and arterial CO2 derived from published medical journals articles to create two conditions: 1. Successful extubation: normal lung mechanic, extreme anxiety; old normal adult, extreme irregular breathing pattern (Cheyne-Stokes), restrictive lung disease; 2. Unsuccessful extubation: altered pulmonary mechanics with and without ineffective inspiratory efforts. RESULTS: Patients with successful extubation, extreme anxiety, moderate irregular breathing pattern and unsuccessful extubation were properly diagnosed by all modes. Patients with Cheyne-Stokes were improperly diagnosed by all modes, but the Smartcare® mode properly diagnosed when the neurologic disorder option was activated. Only Smartcare® properly diagnosed the patient with rapid shallow breathing due to restrictive lung disease. Only MRV improperly diagnosed the patient with ineffective inspiratory efforts. The pressure support level that each mode stabilized varied. ASV® and MRV® reached a stable pressure support level faster than Smartcare®. However, especially for ASV®, there was not stabilization oscillation of the pressure support level over a large range. CONCLUSIONS: The three automated weaning modes performed properly in most patients, even in challenging conditions, as extreme anxiety. Patients with rapid shallow breathing due to restrictive lung disease, ineffective inspiratory efforts and Cheyne-Stokes were improperly diagnosed depending on the mode. ASV® and MRV® have faster responses, but they presented large pressure support level variation, especially the ASV® mode

A Identificação de Sistemas é uma tarefa significativa em termos de tempo e custo no trabalho de implementação de sistemas de controle que usam Controle Preditivo baseado em Modelos (MPC). Após a implementação, o controlador tende a permanecer com o mesmo modelo por muito tempo, ignorando mudanças que tenham ocorrido com o processo, perdendo qualidade e podendo até ser abandonado. Este trabalho propõe uma metodologia simples e eficaz para se proceder à reidentificação de uma planta industrial que use MPC mantendo o processo em malha fechada. Os principais aspectos deste problema são discutidos, e as escolhas que foram feitas para a realização dos experimentos e obtenção dos modelos são explicadas. Apresenta-se um caso em Matlab sobre um sistema 2x2 cobrindo diferentes situações, e é feita uma comparação de identificação realizada através de sinais PRBS e de testes com degraus, sempre em malha fechada. Aplica-se a metodologia a um controlador industrial, e os modelos identificados são introduzidos no controlador. O princípio básico desta metodologia consiste em efetuar perturbações multivariáveis nos set-points ou restrições ativas das controladas e determinar o modelo através da estrutura ARX. Entre as vantagens da metodologia proposta, estão a facilidade de automatizar a identificação do processo e a garantia de manter o processo sob controle durante os testes. / System identification is a major task in the process of implementing Model-based Predictive Control (MPC) algorithms in industrial applications. Once the controller is working, there is a tendency to leave it with the original model for a long time, neglecting changes to the process during this time, leading to performance degradation. This work proposes a simple and effective methodology to re-identify plants under MPC in closed loop. The main issues concerning this problem are discussed, and choices for experiments are made. A Matlab case involving a 2x2 problem is presented, covering a range of different situations, and a comparison between identification using PRBS reference signals and standard step tests is shown. An industrial case is studied, applying the proposed method to a real situation, re-identifying an existing MPC model and reconfiguring it afterwards. This methodology is based on the application of multivariable perturbations on the controlled variables set-points or active restrictions, obtaining an ARX model structure. It uses an automatic process identification proceeding, keeping the process under control along the tests.

Na implementação de controladores MPC, o desenvolvimento e a definição dos modelos do processo é a etapa mais crítica e a que mais consome tempo. Normalmente, os modelos são obtidos através de testes de identificação realizados na planta, onde se observam as respostas em malha aberta das variáveis controladas a perturbações introduzidas individualmente nas variáveis manipuladas. Por este motivo, a aplicação das técnicas de identificação em malha fechada a controladores MPC com restrições nas entradas e/ou saídas é, reconhecidamente, uma área de aplicação de interesse crescente. Neste trabalho é estudada a modificação do controlador MPC convencional através da inclusão de uma nova restrição de excitação em adição às restrições normais do controlador, com a finalidade de perturbar o processo de forma controlada, propiciando a identificação em malha fechada de modelos mais precisos do processo, a partir de modelos aproximados. São desenvolvidas quatro abordagens para implementação desta filosofia e apresentadas simulações para vários casos teóricos, utilizando modelos de dois processos industriais obtidos de artigos recentes relacionados a controle multivariável com incertezas nos modelos. Os resultados das simulações indicam que os dados produzidos permitiram a correta identificação dos modelos tanto no caso nominal (modelo igual à planta) quanto para casos onde a planta era diferente do modelo empregado para as predições do MPC. / In MPC implementation, the process models development and definition is the most critical and time consuming task. Normally, the models are obtained through plant identification tests where perturbations are individually introduced in the manipulated variable while the controlled variable open-loop behavior is observed. For this reason, the application of closed-loop identification techniques to MPC controllers with input or output constraints is a growing interest area. This work studies the traditional MPC controller modification with the inclusion of a new excitation constraint, in addition to input or output constraints, whose function is to perturb the process in a controlled way, permitting the closed-loop identification of more precise models, based on known approximated models. Four implementation methodologies are developed and some simulated theoretical cases are presented using models of two industrial processes extracted from recent papers related to multivariable control with models uncertainty. The simulation results show that the obtained datasets allow the identification of the correct model, both in the nominal case (when the model used by MPC is the true model of the plant) and in the uncertain case, where the model used by MPC is different from the true model.