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Depression is one of the top ten health problems in the world, affecting millions of Canadians. Research indicates that exercise is an effective treatment for depression but it is not clear on exactly how and why it works. Animal studies show that exercise improves the ability of the brain to function. It can even lead to new cell formation in a part of the brain called the hippocampus, which is important for memory processing. This study is investigating whether exercise may also improve hippocampal function in depressed humans. One way exercise may improve brain function is by normalizing levels of the hormone cortisol, and its toxic effects on the hippocampus. Exercise may also normalize levels of biochemical markers called cytokines involved in inflammation, while improving levels of growth factors important to brain cell function. This feasibility study aimed to develop protocols to investigate changes in hippocampal activity while participants are performing memory tests involving association of images and words in a functional magnetic resonance scanner before and after a 12 week exercise program. It also aimed to develop and validate protocols to measure changes in cortisol, cytokines and growth factors which are likely to be affected by exercise. Our preliminary imaging results revealed hippocampal dysregulation in the depressed brain, and biomarker analysis revealed abnormal concentrations of interleukin-6, vascular endothelial growth factor and salivary cortisol when compared to normal healthy controls. However, following the 12-week exercise program a more normalized pattern of hippocampal activation associated with successful memory encoding was observed. Additionally, biomarker concentrations either resembled or were closer to normal healthy values. Over the long term, the project arising from this feasibility study has the potential to provide a tool to improve exercise prescription, to predict exercise responders and to guide development of combined treatment approaches related to biochemical markers in order to optimize depression outcomes for Canadians. / UOIT

PIM - uma técnica onde elementos computacionais são adicionados perto, ou idealmente, dentro de dispositivos de memória - foi uma das tentativas criadas durante os anos 1990 visando mitigar o notório memory wall problem. Hoje em dia, com o amadurecimento do processo de integração 3D, um novo horizonte para novas arquiteturas PIM pode ser explorado. Para investigar este novo cenário, pesquisadores dependem de simuladores em software para navegar pelo espaço de exploração de projeto. Hoje, a maioria dos trabalhos que focam em PIM, implementam simuladores locais para realizar seus experimentos. Porém, esta metodologia pode reduzir a produtividade e reprodutibilidade. Neste trabalho, nós mostramos o desenvolvimento de um simulador de PIM preciso, modular e parametrizável. Nosso simulador, chamado CLAPPS, visa a arquitetura de memória HMC, uma memória 3D popular, que é amplamente utilizada em aceleradores PIM do estado da arte. Nós desenvolvemos nosso mecanismo utilizando a linguagem de programação SystemC, o que permite uma simulação paralela nativamente. A principal contribuição do nosso trabalho se baseia em desenvolver a interface amigável que permite a fácil exploração de arquiteturas PIM. Para avaliar o nosso sistema, nós implementamos um modulo de PIM que pode executar operações vetoriais com diferente tamanhos de operandos utilizando o proposto conjunto de ferramentas. / PIM - a technique which computational elements are added close, or ideally, inside memory devices - was one of the attempts created during the 1990s to try to mitigate the memory wall problem. Nowadays, with the maturation of 3D integration technologies, a new landscape for novel PIM architectures can be investigated. To exploit this new scenario, researchers rely on software simulators to navigate throughout the design evaluation space. Today, most of the works targeting PIM implement in-house simulators to perform their experiments. However, this methodology might hurt overall productivity, while it might also preclude replicability. In this work, we showed the development of a precise, modular and parametrized PIM simulation environment. Our simulator, named CLAPPS, targets the HMC architecture, a popular 3D-stacked memory widely employed in state-of-the-art PIM accelerators. We have designed our mechanism using the SystemC programming language, which allows native parallel simulation. The primary contribution of our work lies in developing a user-friendly interface to allow easy PIM architectures exploitation. To evaluate our system, we have implemented a PIM module that can perform vector operations with different operand sizes using the proposed set of tools.

In this paper, we develop a novel index structure to support efficient approximate k-nearest neighbor (KNN) query in high-dimensional databases. In high-dimensional spaces, the computational cost of the distance (e.g., Euclidean distance) between two points contributes a dominant portion of the overall query response time for memory processing. To reduce the distance computation, we first propose a structure (BID) using BIt-Difference to answer approximate KNN query. The BID employs one bit to represent each feature vector of point and the number of bit-difference is used to prune the further points. To facilitate real dataset which is typically skewed, we enhance the BID mechanism with clustering, cluster adapted bitcoder and dimensional weight, named the BID⁺. Extensive experiments are conducted to show that our proposed method yields significant performance advantages over the existing index structures on both real life and synthetic high-dimensional datasets. / Singapore-MIT Alliance (SMA)

PIM - uma técnica onde elementos computacionais são adicionados perto, ou idealmente, dentro de dispositivos de memória - foi uma das tentativas criadas durante os anos 1990 visando mitigar o notório memory wall problem. Hoje em dia, com o amadurecimento do processo de integração 3D, um novo horizonte para novas arquiteturas PIM pode ser explorado. Para investigar este novo cenário, pesquisadores dependem de simuladores em software para navegar pelo espaço de exploração de projeto. Hoje, a maioria dos trabalhos que focam em PIM, implementam simuladores locais para realizar seus experimentos. Porém, esta metodologia pode reduzir a produtividade e reprodutibilidade. Neste trabalho, nós mostramos o desenvolvimento de um simulador de PIM preciso, modular e parametrizável. Nosso simulador, chamado CLAPPS, visa a arquitetura de memória HMC, uma memória 3D popular, que é amplamente utilizada em aceleradores PIM do estado da arte. Nós desenvolvemos nosso mecanismo utilizando a linguagem de programação SystemC, o que permite uma simulação paralela nativamente. A principal contribuição do nosso trabalho se baseia em desenvolver a interface amigável que permite a fácil exploração de arquiteturas PIM. Para avaliar o nosso sistema, nós implementamos um modulo de PIM que pode executar operações vetoriais com diferente tamanhos de operandos utilizando o proposto conjunto de ferramentas. / PIM - a technique which computational elements are added close, or ideally, inside memory devices - was one of the attempts created during the 1990s to try to mitigate the memory wall problem. Nowadays, with the maturation of 3D integration technologies, a new landscape for novel PIM architectures can be investigated. To exploit this new scenario, researchers rely on software simulators to navigate throughout the design evaluation space. Today, most of the works targeting PIM implement in-house simulators to perform their experiments. However, this methodology might hurt overall productivity, while it might also preclude replicability. In this work, we showed the development of a precise, modular and parametrized PIM simulation environment. Our simulator, named CLAPPS, targets the HMC architecture, a popular 3D-stacked memory widely employed in state-of-the-art PIM accelerators. We have designed our mechanism using the SystemC programming language, which allows native parallel simulation. The primary contribution of our work lies in developing a user-friendly interface to allow easy PIM architectures exploitation. To evaluate our system, we have implemented a PIM module that can perform vector operations with different operand sizes using the proposed set of tools.

PIM - uma técnica onde elementos computacionais são adicionados perto, ou idealmente, dentro de dispositivos de memória - foi uma das tentativas criadas durante os anos 1990 visando mitigar o notório memory wall problem. Hoje em dia, com o amadurecimento do processo de integração 3D, um novo horizonte para novas arquiteturas PIM pode ser explorado. Para investigar este novo cenário, pesquisadores dependem de simuladores em software para navegar pelo espaço de exploração de projeto. Hoje, a maioria dos trabalhos que focam em PIM, implementam simuladores locais para realizar seus experimentos. Porém, esta metodologia pode reduzir a produtividade e reprodutibilidade. Neste trabalho, nós mostramos o desenvolvimento de um simulador de PIM preciso, modular e parametrizável. Nosso simulador, chamado CLAPPS, visa a arquitetura de memória HMC, uma memória 3D popular, que é amplamente utilizada em aceleradores PIM do estado da arte. Nós desenvolvemos nosso mecanismo utilizando a linguagem de programação SystemC, o que permite uma simulação paralela nativamente. A principal contribuição do nosso trabalho se baseia em desenvolver a interface amigável que permite a fácil exploração de arquiteturas PIM. Para avaliar o nosso sistema, nós implementamos um modulo de PIM que pode executar operações vetoriais com diferente tamanhos de operandos utilizando o proposto conjunto de ferramentas. / PIM - a technique which computational elements are added close, or ideally, inside memory devices - was one of the attempts created during the 1990s to try to mitigate the memory wall problem. Nowadays, with the maturation of 3D integration technologies, a new landscape for novel PIM architectures can be investigated. To exploit this new scenario, researchers rely on software simulators to navigate throughout the design evaluation space. Today, most of the works targeting PIM implement in-house simulators to perform their experiments. However, this methodology might hurt overall productivity, while it might also preclude replicability. In this work, we showed the development of a precise, modular and parametrized PIM simulation environment. Our simulator, named CLAPPS, targets the HMC architecture, a popular 3D-stacked memory widely employed in state-of-the-art PIM accelerators. We have designed our mechanism using the SystemC programming language, which allows native parallel simulation. The primary contribution of our work lies in developing a user-friendly interface to allow easy PIM architectures exploitation. To evaluate our system, we have implemented a PIM module that can perform vector operations with different operand sizes using the proposed set of tools.

6 Summary Simultaneous interpreting is a very complex cognitive process. Daniel Gile's Effort Model is an attempt to describe in a schematic way the various competing processes that simultaneous interpreting is composed of. The model is based on findings from cognitive psychology, especially those relating to working memory and the limited processing capacity of the human mind. It defines the process of simultaneous interpreting as a combination of three individual, yet coinciding efforts (the Listening and Analysis Effort, the Production Effort, the Memory Effort), which require a certain amount of processing capacity to assure quality interpreting performance. Problem triggers can cause saturation of the interpreter's processing capacity to occur. Saturation manifests itself either by failure sequences or by the deterioration of the interpreter's performance, immediately or at a distance. The focus of our thesis is on processing capacity saturation due to numbers in simultaneous interpreting, from the point of view of the Effort Model. The first part of our paper is theoretical and deals with the various aspects of the simultaneous interpreting process, especially those relating to processing capacity, saturation and working memory; as well as with questions of well-known problem triggers, interpreting...

Nearly 80% of children treated for cancer are expected to survive, but not without cost. Survivors face unprecedented challenges associated with long-term consequences of treatment, also called late effects. Approximately half of children treated for cancer are at risk for experiencing cognitive late effects, which typically emerge several years post diagnosis. The nature and extent of cognitive late effects appear to be developmental and related to patient, disease, and treatment variables. However, the relationships between these variables is not well understood because there have been few prospective and longitudinal studies that report on the contributions of these variables over time. This dissertation examined the effects of patient, disease, and treatment variables, as well as their interactions over time on neurocognitive functioning in childhood cancer survivors. It comprises part of a large prospective, randomized clinical trial designed to examine changes in cognitive function over three years as a function of different levels of monitoring of school-based intervention based on individual educational plans (IEPs). This dissertation uniquely contributed a new measure (the Treatment Intensity Rating Scale) that was used to systematically classify treatment severity across different types of cancer and cancer treatments. Participants included 61 children ages 7 to 12 years at enrollment who were two to five years from completion of treatment for a brain tumor, leukemia, or lymphoma. Participants received yearly neuropsychological evaluations for a follow-up period of 3 years. Results of these evaluations were used to develop IEPs. Participants were randomized to have their IEPs monitored on a quarterly or annual basis for the duration of the study. Contrary to the progressive decline in neurocognitive functioning that is typically anticipated in pediatric cancer survivors, analyses revealed relative stability of performance on neurocognitive measures over time. Higher neurocognitive performance was noted in children whose IEPs were monitored more frequently versus less frequently. Results also supported gender-specific risk for late effects, with lower performance on select neurocognitive measures in females compared to males. Results of this study provide encouraging evidence of the positive effects of school-based interventions and their close monitoring. This has important implications for quality of life as these children survive well beyond childhood into adulthood.