This dissertation investigated the acquisition and processing of anaphora by learners of English, using both "offline" methods such as paper-and-pencil written tests and "online" methods such as self-paced reading-for-comprehension. Three experiments were conducted. The first two experiments tested advanced Chinese ESL learners' knowledge and processing of anaphora. The focus of the first experiment was on whether participants automatically use gender and number cues, and verb information to interpret pronouns and reflexives during online processing. The second experiment manipulated gender and pragmatic cues to test whether participants have acquired knowledge of structural constraints on reflexive interpretation (i.e., the binding principles). The third experiment, using a pretest-treatment-posttest design, investigated the efficacy of computer-delivered Processing Instruction (PI) on the acquisition of structural constraints and the use of those constraints during reading. During the pretest, subjects completed a self-paced reading task and a written test. For the treatment, participants learned the grammatical constraints on reflexives through interaction with a computer program. Posttest assessment included one interpretation test, one sentence completion task, and one self-paced reading task. The role of feedback in Computer Assisted Language Learning was also examined. Results showed the following: (1) Advanced L2 learners were more sensitive to certain types of agreement information (gender) than others (number). (2) PI improved L2 learners' knowledge about constraints on reflexives as measured by offline tests. (3) PI led to improvement in learners' processing strategies as measured by online tasks. (4) No significant difference was found between the implicit feedback group and the explicit feedback group in the third experiment. Overall, this research highlights the importance of multiple types of assessment that tap the acquisition of grammatical knowledge as well as the proficiency with which learners use that knowledge during reading comprehension tasks.

Research shows that emotional items are associated with enhanced processing and memory. However, emotional memories are composed of not only memory for the specific emotion-eliciting item, but also other items associated with it, as well as memory for how these items are related. The current thesis utilized verbal report, eye movement monitoring and magnetoencephalography in order to examine how emotions may influence online processing and memory for associated information. It was found that while emotions influenced attention to both the emotion-eliciting item and associated information during the encoding stage, this was not related to subsequent memory performance as indexed by verbal report. It was also found that while emotions impaired detailed memory for associated information, it did not affect the ease or speed at which those memories could be accessed. In using MEG, it was found that emotions may modulate not only how participants’ view associated information, but it may also modulate the type of representation formed. Together, findings from the current work suggests that: (1) emotions influence online processing and memory for associated information; (2) emotions modulate memory for associated information via routes other than overt attention; (3) encoding and retrieval may occur in stages; and (4) memory exerts early influences on processing. The current work shows that emotions modulate online processing of associated neutral information in a top-down manner, independent of differences in its physical properties. Work from this thesis encourages a reconceptualization of emotion, memory and perception and how they relate to one and another. Rather than viewing them as independent modular processes, they may, in fact, be more widely distributed in the brain and interact more closely than previously described. This may be evolutionarily adaptive allowing us to quickly and efficiently form memories for emotional events/scenes that can later guide perception and behaviour.

Research shows that emotional items are associated with enhanced processing and memory. However, emotional memories are composed of not only memory for the specific emotion-eliciting item, but also other items associated with it, as well as memory for how these items are related. The current thesis utilized verbal report, eye movement monitoring and magnetoencephalography in order to examine how emotions may influence online processing and memory for associated information. It was found that while emotions influenced attention to both the emotion-eliciting item and associated information during the encoding stage, this was not related to subsequent memory performance as indexed by verbal report. It was also found that while emotions impaired detailed memory for associated information, it did not affect the ease or speed at which those memories could be accessed. In using MEG, it was found that emotions may modulate not only how participants’ view associated information, but it may also modulate the type of representation formed. Together, findings from the current work suggests that: (1) emotions influence online processing and memory for associated information; (2) emotions modulate memory for associated information via routes other than overt attention; (3) encoding and retrieval may occur in stages; and (4) memory exerts early influences on processing. The current work shows that emotions modulate online processing of associated neutral information in a top-down manner, independent of differences in its physical properties. Work from this thesis encourages a reconceptualization of emotion, memory and perception and how they relate to one and another. Rather than viewing them as independent modular processes, they may, in fact, be more widely distributed in the brain and interact more closely than previously described. This may be evolutionarily adaptive allowing us to quickly and efficiently form memories for emotional events/scenes that can later guide perception and behaviour.

Submitted by Renata Lopes (renatasil82@gmail.com) on 2017-04-25T14:05:10Z No. of bitstreams: 1 joaopaulobittencourtdasilveiraduarte.pdf: 8307204 bytes, checksum: a026db8104dd8767f6e5b0fc71d452e9 (MD5) / Approved for entry into archive by Adriana Oliveira (adriana.oliveira@ufjf.edu.br) on 2017-04-25T15:27:51Z (GMT) No. of bitstreams: 1 joaopaulobittencourtdasilveiraduarte.pdf: 8307204 bytes, checksum: a026db8104dd8767f6e5b0fc71d452e9 (MD5) / Made available in DSpace on 2017-04-25T15:27:51Z (GMT). No. of bitstreams: 1 joaopaulobittencourtdasilveiraduarte.pdf: 8307204 bytes, checksum: a026db8104dd8767f6e5b0fc71d452e9 (MD5) Previous issue date: 2015-08-27 / Este trabalho apresenta um estudo sobre técnicas de deconvolução de sinais para a reconstrução online de energia no primeiro nível de trigger do calorímetro hadrônico (TileCal) do ATLAS. O ambiente de alta luminosidade, previsto para ocorrer nos próximos anos no colisionador de partículas LHC, aumenta a probabilidade de ocorrência de colisões adjacentes, promovendo o efeito de empilhamento de sinais. O algoritmo atualmente utilizado para a reconstrução de energia não é robusto a este efeito. Neste trabalho, o TileCal é interpretado como um canal de comunicação, cuja a resposta ao impulso deve ser compensada a fim de remover o efeito de empilhamento e recuperar a informação de energia depositada em cada colisão. Os métodos desenvolvidos requisitam uma implementação online. As FPGAs, por serem dispositivos reconfiguráveis e de alta velocidade, foram escolhidas para implementação destes algoritmos. Assim, neste trabalho avaliou-se dois tipos de técnicas de deconvolução, uma direta baseada em filtros FIR e outra baseada em métodos iterativos. O segundo tipo de técnica, permite uma melhora de desempenho na reconstrução pela possibilidade de se utilizar um conhecimento especialista de que a energia reconstruída deve ser sempre positiva. Os resultados da avaliação mostram que os métodos propostos apresentam maior desempenho, em alta luminosidade, do que o método atualmente implementado. Como esperado, os métodos iterativos reconstroem a energia com menor erro quando comparados às técnicas baseadas em filtros FIR. Porém, com relação a implementação, as técnicas iterativas são de maior complexidade e utilizam mais recursos de hardware. / This work presents a study of deconvolution techniques to be used in the online energy reconstruction for the ATLAS hadronic calorimeter (TileCal) first level trigger system. The high-luminosity environment, foreseen for the next years of operation of the LHC particle collider, increases the probability of observe adjacent collisions, promoting the signal superposition effect. The current algorithm for energy reconstruction is not robust against this pile-up effect. In this work, the TileCal is considered as a communication channel whose impulse response must be compensated in order to remove the pile-up effect and to recover the deposited energy information at each collision. The developed methods require an online implementation. Since FPGAs are suitable for high-speed applications, they are chosen to be used in the ATLAS trigger system. Therefore, in this work two different online deconvolution techniques were tested, a direct FIR filter implementation and techniques based on iterative processes. The later outperforms the former due to the possibility of imposing a constraint for reconstructing only positive energies, which is know to reflect the reality. The results have shown that the proposed methods present better reconstruction performance than the current employed method when the environment presents superposition effect (high luminosity). As expected, the iterative methods present smaller errors than the direct FIR methods. However, regarding the FPGA implementation, the iterative techniques have a higher computational cost and uses more hardware resources.