Introdução: Ruminação é a perseveração mal-adaptativa de pensamentos auto-centrados. Evidências sinalizam que ela está associada com início e manutenção de episódios depressivos, e ocorre em múltiplos transtornos mentais. A ruminação está associada com marcadores de desenvolvimento psicopatológico, como volumetria cerebral, memória, genes do BDNF e serotonina. É necessário aprofundar o conhecimento da ruminação enquanto traço dimensional, e conhecer melhor sua associação com variáveis sóciodemográficas, biológicas e clínicas para entender quando passa a ser um sintoma. Entretanto, aferi-la é um desafio, considerando que só existem escalas psicométricas. A mais utilizada, Ruminative Response Scale (RRS), foi validada em amostras não-clínicas. Objetivos: Avaliar ruminação transdiagnosticamente e determinar a validade de constructo da RRS em amostra clínica, buscando determinar fatores sócio-demográficos, clínicos e neurobiológicos associados a maiores escores de ruminação. Métodos: Estudo transversal, amostra não-probabilística. Foram convidados a participar 944 pacientes em atendimento psiquiátrico ambulatorial no HCPA entre março/2015 e junho/2016, maiores de 18 anos, que soubessem ler e escrever, e portadores de transtornos bipolares, depressão, esquizofrenia, esquizoafetivo, ansiedade generalizada, pânico, fobia específica e obsessivocompulsivo. Foram excluídos 373 com doenças que alteram resposta inflamatória, dependência química, gravidez, lactação, doenças neurológicas, vasculares e degenerativas. Recusaram-se a participar 254. Foram incluídos 317 pacientes, e 200 completaram a coleta de dados, que foi realizada em 4 etapas: 1) perfil sócio-demográfico e escalas auto-aplicáveis: ruminação, preocupação e funcionalidade; 2) amostras de sangue e entrevista clínica para aplicação das escalas de sintomas: depressão, mania, ansiedade e gravidade; 3) confirmação diagnóstica; e 4) processamento, armazenamento e análises bioquímicas das amostras de sangue. No primeiro artigo, revisamos sistematicamente a literatura sobre ruminação nos transtornos bipolares. No segundo, determinamos as validades de construto e externa da RRS. No terceiro, usamos machine learning para encontrar padrões de ruminação e determinar quais variáveis associadas preveem ruminação. Resultados: Ruminação está presente em todas as fases do transtorno bipolar, e é um sintoma estável independente do estado de humor, apesar de ter relação estreia com ele. Verificou-se também que mulheres ruminam mais que homens. Os escores de ruminação foram menores nos portadores de esquizofrenia que nos com depressão maior, bipolaridade e ansiedade. RRS apresentou boa confiabilidade, com 2-fatores correlacionados, brooding e ponderação, que apresentaram similaridade nas correlações com medidas clínicas, confirmando a validade externa transdiagnóstica. Por fim, encontrou-se que as variáveis associadas aos pacientes que mais ruminam são preocupação, sintomas de ansiedade generalizada e depressão, gravidade, nível socioeconômico e diagnóstico atual de pânico, sinalizando que ruminação pode ser um marcador de maior sensibilidade à ansiedade. Discussão: Ruminação parece ser um sintoma transdiagnóstico marcador de sofrimento. Os resultados desta tese contribuem para ampliar a discussão sobre diagnóstico psiquiátrico, agregando evidências para aprimorar as definições de limites e sobreposições diagnósticas entre as doenças mentais em que a ruminação ocorre. Por fim, conhecer melhor os mecanismos bioquímicos e clínicos envolvidos na ruminação contribuem na compreensão sobre quando ela deixa de ser um traço normal e vira um sintoma que necessita de tratamento. / Introduction: Rumination has been described as maladaptive perseveration of self-centered thoughts. Evidence indicates that rumination is associated with onset and maintenance of depressive episodes, it’s present in several mental disorders. Rumination is associated with markers of development of psychopathology, such as cerebral volumetry, memory, BDNF and serotonin genes. Measuring rumination is a challenge, considering that are available only psychometric scales. The most used, the Ruminative Responses Scale (RRS), was validated on non-clinical samples. Objectives: To evaluate transdiagnostically the rumination and to determine construct validity of the RRS in outpatients, in order to determine which associated factors lead the patients to ruminate. Methods: Cross-sectional study, non-probabilistic sample. A total of 944 patients in psychiatric outpatient treatment at HCPA between March / 2015 and June / 2016, major than 18 years old, knowing read and write, presenting bipolar disorder, schizophrenia, schizoaffective disorder, generalized anxiety disorder, panic disorder, phobia specific and obsessive-compulsive disorder were invited to participate. We excluded 373 patients with diseases that alter inflammatory response, chemical dependence, pregnancy, lactation, neurological, vascular and degenerative diseases. Two hundred fifty four refused to participate, 317 were included, and 200 completed the data collection, which was performed in 4 stages: 1) socio-demographic profile and self-applicable scales: rumination, worry and functionality; 2) blood samples and clinical interview for the application of symptom scales: depression, mania, anxiety and severity; 3) diagnostic confirmation; and 4) processing, storage and biochemical analyzes of blood samples. In the first article, we systematically reviewed the literature on rumination in bipolar disorders. In the second, we evaluated construct and external validity of RRS. In the third, we used machine learning algorithms to find patterns of rumination and to determine which associated variables predict rumination. Results: Rumination is present in all phases of bipolar disorder, it is a stable symptom, independent of mood, despite it has close relationship with it. It has also been found that women ruminate more than men. Rumination scores were lower in patients with schizophrenia than in major depression, bipolarity and anxiety patients. RRS presented good reliability, with correlated 2-factors, brooding and pondering, which presented similar correlations with clinical measures, confirming the external transdiagnostic validity. Finally, it was found that the variables associated with the greater scores of rumination are worry, symptoms of generalized anxiety and depression, severity of symptoms, socioeconomic level and current diagnosis of panic, signaling that rumination may be a marker of greater sensitivity to anxiety. Discussion: Rumination seems to be a transdiagnostic symptom of suffering. The results of this thesis contribute to broadening the discussion about psychiatric diagnostic, adding evidence to improve the definitions of limits and diagnostic overlaps between mental illnesses in which rumination occurs. Finally, a better understanding of the biochemical and clinical mechanisms involved in rumination may contribute to understanding of when rumination ceases to be a normal trait and becomes a symptom that requires treatment.

Introdução: Ruminação é a perseveração mal-adaptativa de pensamentos auto-centrados. Evidências sinalizam que ela está associada com início e manutenção de episódios depressivos, e ocorre em múltiplos transtornos mentais. A ruminação está associada com marcadores de desenvolvimento psicopatológico, como volumetria cerebral, memória, genes do BDNF e serotonina. É necessário aprofundar o conhecimento da ruminação enquanto traço dimensional, e conhecer melhor sua associação com variáveis sóciodemográficas, biológicas e clínicas para entender quando passa a ser um sintoma. Entretanto, aferi-la é um desafio, considerando que só existem escalas psicométricas. A mais utilizada, Ruminative Response Scale (RRS), foi validada em amostras não-clínicas. Objetivos: Avaliar ruminação transdiagnosticamente e determinar a validade de constructo da RRS em amostra clínica, buscando determinar fatores sócio-demográficos, clínicos e neurobiológicos associados a maiores escores de ruminação. Métodos: Estudo transversal, amostra não-probabilística. Foram convidados a participar 944 pacientes em atendimento psiquiátrico ambulatorial no HCPA entre março/2015 e junho/2016, maiores de 18 anos, que soubessem ler e escrever, e portadores de transtornos bipolares, depressão, esquizofrenia, esquizoafetivo, ansiedade generalizada, pânico, fobia específica e obsessivocompulsivo. Foram excluídos 373 com doenças que alteram resposta inflamatória, dependência química, gravidez, lactação, doenças neurológicas, vasculares e degenerativas. Recusaram-se a participar 254. Foram incluídos 317 pacientes, e 200 completaram a coleta de dados, que foi realizada em 4 etapas: 1) perfil sócio-demográfico e escalas auto-aplicáveis: ruminação, preocupação e funcionalidade; 2) amostras de sangue e entrevista clínica para aplicação das escalas de sintomas: depressão, mania, ansiedade e gravidade; 3) confirmação diagnóstica; e 4) processamento, armazenamento e análises bioquímicas das amostras de sangue. No primeiro artigo, revisamos sistematicamente a literatura sobre ruminação nos transtornos bipolares. No segundo, determinamos as validades de construto e externa da RRS. No terceiro, usamos machine learning para encontrar padrões de ruminação e determinar quais variáveis associadas preveem ruminação. Resultados: Ruminação está presente em todas as fases do transtorno bipolar, e é um sintoma estável independente do estado de humor, apesar de ter relação estreia com ele. Verificou-se também que mulheres ruminam mais que homens. Os escores de ruminação foram menores nos portadores de esquizofrenia que nos com depressão maior, bipolaridade e ansiedade. RRS apresentou boa confiabilidade, com 2-fatores correlacionados, brooding e ponderação, que apresentaram similaridade nas correlações com medidas clínicas, confirmando a validade externa transdiagnóstica. Por fim, encontrou-se que as variáveis associadas aos pacientes que mais ruminam são preocupação, sintomas de ansiedade generalizada e depressão, gravidade, nível socioeconômico e diagnóstico atual de pânico, sinalizando que ruminação pode ser um marcador de maior sensibilidade à ansiedade. Discussão: Ruminação parece ser um sintoma transdiagnóstico marcador de sofrimento. Os resultados desta tese contribuem para ampliar a discussão sobre diagnóstico psiquiátrico, agregando evidências para aprimorar as definições de limites e sobreposições diagnósticas entre as doenças mentais em que a ruminação ocorre. Por fim, conhecer melhor os mecanismos bioquímicos e clínicos envolvidos na ruminação contribuem na compreensão sobre quando ela deixa de ser um traço normal e vira um sintoma que necessita de tratamento. / Introduction: Rumination has been described as maladaptive perseveration of self-centered thoughts. Evidence indicates that rumination is associated with onset and maintenance of depressive episodes, it’s present in several mental disorders. Rumination is associated with markers of development of psychopathology, such as cerebral volumetry, memory, BDNF and serotonin genes. Measuring rumination is a challenge, considering that are available only psychometric scales. The most used, the Ruminative Responses Scale (RRS), was validated on non-clinical samples. Objectives: To evaluate transdiagnostically the rumination and to determine construct validity of the RRS in outpatients, in order to determine which associated factors lead the patients to ruminate. Methods: Cross-sectional study, non-probabilistic sample. A total of 944 patients in psychiatric outpatient treatment at HCPA between March / 2015 and June / 2016, major than 18 years old, knowing read and write, presenting bipolar disorder, schizophrenia, schizoaffective disorder, generalized anxiety disorder, panic disorder, phobia specific and obsessive-compulsive disorder were invited to participate. We excluded 373 patients with diseases that alter inflammatory response, chemical dependence, pregnancy, lactation, neurological, vascular and degenerative diseases. Two hundred fifty four refused to participate, 317 were included, and 200 completed the data collection, which was performed in 4 stages: 1) socio-demographic profile and self-applicable scales: rumination, worry and functionality; 2) blood samples and clinical interview for the application of symptom scales: depression, mania, anxiety and severity; 3) diagnostic confirmation; and 4) processing, storage and biochemical analyzes of blood samples. In the first article, we systematically reviewed the literature on rumination in bipolar disorders. In the second, we evaluated construct and external validity of RRS. In the third, we used machine learning algorithms to find patterns of rumination and to determine which associated variables predict rumination. Results: Rumination is present in all phases of bipolar disorder, it is a stable symptom, independent of mood, despite it has close relationship with it. It has also been found that women ruminate more than men. Rumination scores were lower in patients with schizophrenia than in major depression, bipolarity and anxiety patients. RRS presented good reliability, with correlated 2-factors, brooding and pondering, which presented similar correlations with clinical measures, confirming the external transdiagnostic validity. Finally, it was found that the variables associated with the greater scores of rumination are worry, symptoms of generalized anxiety and depression, severity of symptoms, socioeconomic level and current diagnosis of panic, signaling that rumination may be a marker of greater sensitivity to anxiety. Discussion: Rumination seems to be a transdiagnostic symptom of suffering. The results of this thesis contribute to broadening the discussion about psychiatric diagnostic, adding evidence to improve the definitions of limits and diagnostic overlaps between mental illnesses in which rumination occurs. Finally, a better understanding of the biochemical and clinical mechanisms involved in rumination may contribute to understanding of when rumination ceases to be a normal trait and becomes a symptom that requires treatment.

<div>The innovations in Magnetic Resonance Imaging (MRI) in the recent decades have given rise to large open-source datasets. MRI affords researchers the ability to look at both structure and function of the human brain. This dissertation will make use of one of these large open-source datasets, the Human Connectome Project (HCP), to study the structural and functional connectivity in the brain.</div><div>Communication processes within the human brain at different cognitive states are neither well understood nor completely characterized. We assess communication processes in the human connectome using ant colony-inspired cooperative learning algorithm, starting from a source with no <i>a priori</i> information about the network topology, and cooperatively searching for the target through a pheromone-inspired model. This framework relies on two parameters, namely <i>pheromone</i> and <i>edge perception</i>, to define the cognizance and subsequent behaviour of the ants on the network and the communication processes happening between source and target. Simulations with different configurations allow the identification of path-ensembles that are involved in the communication between node pairs. In order to assess the different communication regimes displayed on the simulations and their associations with functional connectivity, we introduce two network measurements, effective path-length and arrival rate. These measurements are tested as individual and combined descriptors of functional connectivity during different tasks. Finally, different communication regimes are found in different specialized functional networks. This framework may be used as a test-bed for different communication regimes on top of an underlying topology.</div><div>The assessment of brain <i>fingerprints</i> has emerged in the recent years as an important tool to study individual differences. Studies so far have mainly focused on connectivity fingerprints between different brain scans of the same individual. We extend the concept of brain connectivity fingerprints beyond test/retest and assess <i>fingerprint gradients</i> in young adults by developing an extension of the differential identifiability framework. To do so, we look at the similarity between not only the multiple scans of an individual (<i>subject fingerprint</i>), but also between the scans of monozygotic and dizygotic twins (<i>twin fingerprint</i>). We have carried out this analysis on the 8 fMRI conditions present in the Human Connectome Project -- Young Adult dataset, which we processed into functional connectomes (FCs) and time series parcellated according to the Schaefer Atlas scheme, which has multiple levels of resolution. Our differential identifiability results show that the fingerprint gradients based on genetic and environmental similarities are indeed present when comparing FCs for all parcellations and fMRI conditions. Importantly, only when assessing optimally reconstructed FCs, we fully uncover fingerprints present in higher resolution atlases. We also study the effect of scanning length on subject fingerprint of resting-state FCs to analyze the effect of scanning length and parcellation. In the pursuit of open science, we have also made available the processed and parcellated FCs and time series for all conditions for ~1200 subjects part of the HCP-YA dataset to the scientific community.</div><div>Lastly, we have estimated the effect of genetics and environment on the original and optimally reconstructed FC with an ACE model.</div>

Les réseaux neuronaux profonds sont des outils prometteurs pour l'évaluation de la biodiversité aviaire, en particulier pour la détection des chants et la classification acoustique des espèces. Toutefois, on connaît mal l’étendue de leur capacité de généralisation face à la variation intraspécifique présente dans les chants d’oiseaux, ce qui pourrait mener à des biais. Notre étude porte sur l'évaluation des performances de BirdNET, un réseau neuronal profond, pour le traitement d’un corpus d'enregistrements audio caractérisés par une variation intraspécifique significative, en utilisant l’exemple du chant du bruant des prés (Passerculus sandwichensis). Dans la population de l'île de Kent, au Nouveau-Brunswick, les individus sont suivis et enregistrés grâce à leurs bagues de couleur et la présence de microdialectes est solidement documentée. Nous avons recueilli et annoté 69 606 chants provenant de 52 individus et analysé ces données à l'aide d’une version récente de BirdNET. Nos résultats révèlent que BirdNET démontre une précision globale suffisante, prédisant correctement 81,9 % des chants, ce qui dépasse les résultats rapportés par ses développeurs. Toutefois, nous avons observé une variation considérable dans les scores de confiance et les taux de prédiction exactes entre les individus, ce qui suggère des biais potentiels. Cependant, nos recherches n'ont pas mis en évidence de variation entre les résultats des différents microdialectes, ce qui souligne la relative robustesse de l'algorithme. Nous avançons que la variation observée entre les individus est due au fait que certains d’entre eux chantent systématiquement plus près des microphones, résultant en des chants plus clairs donc plus faciles à identifier. Pour mieux comprendre le processus de prise de décision de BirdNET, nous avons tenté de produire des cartes d'activation de classe, qui constituent un outil précieux pour identifier les éléments d’un chant qui déterminent une prédiction. Cependant, il ne nous a pas été possible d’obtenir des cartes d’activation de classe d’après la version actuellement disponible du code de BirdNET sans avoir recours à des connaissances avancées en informatique. L'accès à des outils explicatifs adaptés aux innovations récentes dans les architectures de réseaux neuronaux 4 profonds serait crucial pour mieux interpréter les résultats et renforcer la confiance des utilisateurs. Nos résultats soulignent la nécessité de poursuivre les recherches sur la capacité de généralisation des réseaux neuronaux profonds pour la bioacoustique en utilisant des ensembles de données monospécifiques portant sur de plus longues périodes ou des aires de répartition géographique plus vastes. En outre, l'extension de cette étude à des espèces ayant des répertoires plus importants ou des différences plus subtiles entre le chant des individus pourrait nous informer davantage sur les limites et le potentiel des algorithmes d'apprentissage profond pour la détection et la classification acoustiques des espèces. En conclusion, notre étude démontre les performances prometteuses de BirdNET pour le traitement d'un large corpus de chants de bruants des prés, et confirme son potentiel en tant qu'outil précieux pour l'évaluation de la biodiversité aviaire. Les biais dus aux techniques d’enregistrement et la variation dans les taux de succès observés entre les individus méritent d'être étudiés plus en détail. / Machine learning, particularly deep neural networks, has gained prominence as a valuable tool in ecological studies and wildlife conservation planning. In the field of avian biodiversity assessment, deep neural networks have shown remarkable promise, particularly in acoustic species detection and classification. Despite their success, a critical knowledge gap exists concerning the generalization ability of these algorithms across intraspecific variation in bird song. This raises concerns about potential biases and misinterpretation of results. This study focuses on evaluating the performance of BirdNET, a deep neural network, in processing audio recordings characterized by significant intraspecific variation in the Savannah Sparrow (Passerculus sandwichensis) song. Savannah Sparrows are an ideal candidate for this investigation, given their well-studied population on Kent Island, New Brunswick, Canada. Each male sings a unique, unchanging song throughout its life, and the population exhibits well-documented geographical microdialects. We collected a large corpus of Savannah Sparrow songs using autonomous and focal recorders on Kent Island, yielding a total of 69,606 manually annotated songs from 52 different sparrows. We analyzed the audio data using BirdNET-Analyzer. The resulting confidence scores were used to assess the algorithm's performance across microdialects and individual birds. Our results revealed that BirdNET exhibited considerable overall accuracy, correctly predicting 81.9% of the songs, which surpassed the results reported by the developers of BirdNET. We observed variations in BirdNET's confidence scores among individual birds, suggesting potential biases in its classifications. However, our investigation indicated no evidence of distinct biases towards specific microdialects, highlighting the algorithm's relative robustness across these groups. We suspect that the variation observed amongst individuals is caused by the fact that some were singing consistently closer to microphones, yielding clearer songs. To gain insights into BirdNET's decision-making process, we sought to employ class activation maps, a valuable tool for identifying essential song elements contributing to species predictions. However, we were unable to produce class activation maps from the current version of BirdNET 6 without advanced computer science skills. Access to informative tools adapted to recent innovations in deep neural network architectures for bioacoustic applications is crucial for understanding and interpreting results better. Such tools would enhance user confidence and favour accountability for conservation decisions based on these predictions. Our findings underscore the need for further research investigating the generalization capacity of deep neural networks in bioacoustics on single-species datasets with more extensive intraspecific variation and broader geographical ranges. Additionally, expanding this investigation to species with larger song repertoires or more subtle inter-individual song differences could provide valuable insights into the limits and potential of deep learning algorithms for acoustic species detection and classification. In conclusion, our study demonstrates BirdNET's promising performance in processing a large corpus of Savannah Sparrow songs, highlighting its potential as a valuable tool for avian biodiversity assessment. Biases and variations in confidence scores observed across individual birds warrant further investigation.

No description available.

<p dir="ltr">The absence or limited availability of operational statistics at general aviation airports restricts airport managers and operators from assessing comprehensive operational data. The traditional manual compilation of operational statistics is labor-intensive and lacks the depth and accuracy to depict a holistic picture of a general aviation airport’s operations. This research developed a reliable and efficient approach to address the problem by providing a comprehensive and versatile flight status identification framework. </p><p dir="ltr">Leveraging the BlueSky flight simulation module, the research can generate a synthetic flight database to emulate real-world general aviation aircraft’s flight scenarios. Two neural network architectures, namely, an RNN-GAN network and a refined Seq2Seq network, were explored to examine their capability to reconstruct flight trajectories. The Seq2Seq network, which demonstrated better performance, was further employed to estimate the simulated aircraft’s different metrics, such as internal mechanical metrics and flight phase. Additionally, this research undertook an array of diverse tailored evaluation techniques to assess the efficacy of flight status predictions and conducted comparative analyses between various configurations. </p><p dir="ltr">Furthermore, the research concluded by discussing the future development of the framework, emphasizing its potential for generalization across various flight data applications and scenarios. The enhanced methodology for collecting operational statistics and the analysis tool will enable airport managers and regulators to better receive a comprehensive view of the airport’s operations, facilitating airport planning and development.</p>

<p dir="ltr">With increasing power densities in electronic devices, effective thermal management has become an indispensable aspect of electronic systems design. Although phase change materials (PCMs) have been studied as a potential solution, their integration into microelectronic and high-power devices presents a significant challenge due to low thermal conductivity and lack of effective thermal pathways from the heat source to the heat sink. While much work has focused on integrating thermal storage into heat sinks, this dissertation instead investigates integrating PCMs between the heat source and the heat sink in different configurations. By placing the energy storage closer to the heat source, the thermal resistance is reduced, which improves the overall thermal performance of the device. Specifically, this work explores the efficacy of two approaches: (1) direct embedding of a PCM within the die for mobile electronics applications and (2) integration of an auxiliary composite PCM/copper thermal energy storage (TES) component in combination with active liquid cooling for high-power power electronics modules.</p><p><br></p><p dir="ltr">The first study explores die-level thermal management for microelectronics using PCMs. Silicon chips with PCM embedded within the die are modeled using ParaPower, a fast-analysis tool, and a genetic algorithm is used to efficiently optimize the distribution of high-conductivity silicon pathways and high thermal capacitance PCM zones. A thermal test vehicle (TTV) of a realistic microelectronics form factor with an embedded PCM layer is first designed, and a process is developed to fabricate such a TTV. This study is the first to successfully fabricate a TTV with fully encapsulated PCM and validate its thermal response across various operational scenarios. For temperature cycling tests (where the TTV temperature fluctuates between predetermined hot and cold setpoints), the embedded-PCM TTVs extend the operational time by up to 2.8x compared to a baseline all-silicon TTV. For duty cycling tests (with a fixed duration of the periodic heating pulses and off times), the embedded-PCM TTVs suppress the hotspot temperature rise by up to 14% and stabilize quasi-steady state temperature fluctuations by up to 65% through repeated PCM melting and solidification cycles. Thermal performance enhancements are observed even for high heat fluxes of ~65W/cm² . Specifically, a TTV with an embedded square-shaped PCM reservoir reduces temperature instability by an average of 40% across a range of cycle durations.</p><p><br></p><p dir="ltr">The second study investigates the effectiveness of different integration strategies for an auxiliary composite PCM/copper TES block integrated alongside a cold plate, for thermal management of high-power power electronics modules, specifically for electric vehicles. These systems are evaluated for realistic drive cycles of various driving intensities. Computational results indicate that this approach is most effective when the composite TES block is positioned directly above the heat-generating silicon carbide dies. This configuration excels at stabilizing transient temperature fluctuations and absorbing thermal shocks, achieving reductions of up to approximately ~33% compared to current thermal management techniques. This strategy is particularly effective for stop-and-go drive cycles characterized by high rates of acceleration and deceleration, low average driving speeds, and frequent stops, typical of driving schedules for public transport buses and mail delivery vehicles.</p><p><br></p><p dir="ltr">The results from both thermal management approaches demonstrate that the integration of a PCM cooling solution in close proximity to the heat source can significantly enhance its effectiveness by absorbing power bursts and limiting temperature instability via repeated melting and solidification. The contributions of this dissertation include the development of an effective optimization strategy for generating optimized PCM distributions, which reduces the maximum temperature and temperature oscillations in a device with significant computational efficiency. (The same optimization strategy can be applied to other thermal management design challenges.) Notably, TTVs of realistic microelectronics form factors with embedded PCM were designed, modeled, fabricated, and validated. With the PCM thermal buffers, the engineered solution demonstrated superior performance compared to a baseline all-silicon TTV. The second study into the integration of composite PCM/copper TES blocks into high-power power electronics modules established trade-offs between different architectures across various performance metrics, and highlighted its effectiveness for drive cycles with varying intensities. These findings offer an important contribution to the development of embedded thermal management techniques for electronic systems design, which will be critical for the advancement of next-generation microelectronics and high-power devices.</p>

The purpose of this thesis was to design and evaluate The ContexTable, a context-aware system built into a kitchen table. After establishing the current status of the field of context-aware systems and the hurdles and problems being faced, a functioning prototype system was designed and built. The prototype makes it possible to explore established, untested theory and novel solutions to problems faced in the field.