The time-course of lexical activation in Japanese morphographic word recognition: Evidence for a character-driven processing model

This lexical decision study with eye tracking of Japanese two-kanji-character words investigated the order in which a whole two-character word and its morphographic constituents are activated in the course of lexical access, the relative contributions of the left and the right characters in lexical decision, the depth to which semantic radicals are processed, and how nonlinguistic factors affect lexical processes. Mixed-effects regression analyses of response times and subgaze durations (i.e., first-pass fixation time spent on each of the two characters) revealed joint contributions of morphographic units at all levels of the linguistic structure with the magnitude and the direction of the lexical effects modulated by readers’ locus of attention in a left-to-right preferred processing path. During the early time frame, character effects were larger in magnitude and more robust than radical and whole-word effects, regardless of the font size and the type of nonwords. Extending previous radical-based and character-based models, we propose a task/decision-sensitive character-driven processing model with a level-skipping assumption: Connections from the feature level bypass the lower radical level and link up directly to the higher character level.

Electron Transfer Involving the Phylloquinone (A1) Cofactor of Photosystem I Examined with Time Resolved Absorbance and Electron Paramagnetic Resonance Spectroscopy

The dependence of the electron transfer (ET) rate on the Photosystem I (PSI) cofactor phylloquinone (A1) is studied by time-resolved absorbance and electron paramagnetic resonance (EPR) spectroscopy. Two active branches (A and B) of electron transfer converge to the FX cofactor from the A1A and A1B quinone. The work described in Chapter 5 investigates the single hydrogen bond from the amino acid residue PsaA-L722 backbone nitrogen to A1A for its effect on the electron transfer rate to FX. Room temperature transient EPR measurements show an increase in the rate for the A1A- to FX for the PsaA-L722T mutant and an increased hyperfine coupling to the 2-methyl group of A1A when compared to wild type. The Arrhenius plot of the A1A- to FX ET in the PsaA-L722T mutant suggests that the increased rate is probably the result of a slight change in the electronic coupling between A1A- and FX. The reasons for the non-Arrhenius behavior are discussed. The work discussed in Chapter 6 investigates the directionality of ET at low temperature by blocking ET to the iron-sulfur clusters FX, FA and FB in the menB deletion mutant strain of Synechocyctis sp. PCC 6803, which is unable to synthesize phylloquinone, by incorporating the high midpoint potential (49 mV vs SHE) 2,3-dichloro-1,4-naphthoquinone (Cl2NQ) into the A1A and A1B binding sites. Various EPR spectroscopic techniques were implemented to differentiate between the spectral features created from A and B- branch electron transfer. The implications of this result for the directionality of electron transfer in PS I are discussed. The work discussed in Chapter 7 was done to study the dependence of the heterogeneous ET at low temperature on A1 midpoint potential. The menB PSI mutant contains plastiquinone-9 in the A1 binding site. The solution midpoint potential of the quinone measures 100 mV more positive then wild-type phylloquinone. The irreversible ET to the terminal acceptors FA and FB at low temperature is not controlled by the forward step from A1 to FX as expected due to the thermodynamic differences of the A1 cofactor in the two active branches A and B. Alternatives for the ET heterogeneity are discussed.

Characterizing Dynamic Optimization Benchmarks for the Comparison of Multi-Modal Tracking Algorithms

Population-based metaheuristics, such as particle swarm optimization (PSO), have been employed to solve many real-world optimization problems. Although it is of- ten sufficient to find a single solution to these problems, there does exist those cases where identifying multiple, diverse solutions can be beneficial or even required. Some of these problems are further complicated by a change in their objective function over time. This type of optimization is referred to as dynamic, multi-modal optimization. Algorithms which exploit multiple optima in a search space are identified as niching algorithms. Although numerous dynamic, niching algorithms have been developed, their performance is often measured solely on their ability to find a single, global optimum. Furthermore, the comparisons often use synthetic benchmarks whose landscape characteristics are generally limited and unknown. This thesis provides a landscape analysis of the dynamic benchmark functions commonly developed for multi-modal optimization. The benchmark analysis results reveal that the mechanisms responsible for dynamism in the current dynamic bench- marks do not significantly affect landscape features, thus suggesting a lack of representation for problems whose landscape features vary over time. This analysis is used in a comparison of current niching algorithms to identify the effects that specific landscape features have on niching performance. Two performance metrics are proposed to measure both the scalability and accuracy of the niching algorithms. The algorithm comparison results demonstrate the algorithms best suited for a variety of dynamic environments. This comparison also examines each of the algorithms in terms of their niching behaviours and analyzing the range and trade-off between scalability and accuracy when tuning the algorithms respective parameters. These results contribute to the understanding of current niching techniques as well as the problem features that ultimately dictate their success.