Competing demands for a complex system : photosystem II repair, photoprotection and quantum yield

Photosynthesis in general is a key biological process on Earth and Photo system II (PSII) is an important component of this process. PSII is the only enzyme capable of oxidizing water and is largely responsible for the primordial build-up and present maintenance of the oxygen in the atmosphere. This thesis endeavoured to understand the link between structure and function in PSII with special focus on primary photochemistry, repair/photodamage and spectral characteristics. The deletion of the PsbU subunit ofPSII in cyanobacteria caused a decoupling of the Phycobilisomes (PBS) from PSII, likely as a result of increased rates of PSII photodamage with the PBS decoupling acting as a measure to protect PSII from further damage. Isolated fractions of spinach thylakoid membranes were utilized to characterize the heterogeneity present in the various compartments of the thylakoid membrane. It was found that the pooled PSIILHCII pigment populations were connected in the grana stack and there was also a progressive decrease in the reaction rates of primary photochemistry and antennae size of PSII as the sample origin moved from grana to stroma. The results were consistent with PSII complexes becoming damaged in the grana and being sent to the stroma for repair. The dramatic quenching of variable fluorescence and overall fluorescent yield of PSII in desiccated lichens was also studied in order to investigate the mechanism by which the quenching operated. It was determined that the source of the quenching was a novel long wavelength emitting external quencher. Point mutations to amino acids acting as ligands to chromophores of interest in PSII were utilized in cyanobacteria to determine the role of specific chromophores in energy transfer and primary photochemistry. These results indicated that the Hl14 ligated chlorophyll acts as the 'trap' chlorophyll in CP47 at low temperature and that the Q130E mutation imparts considerable changes to PSII electron transfer kinetics, essentially protecting the complex via increased non-radiative charge Photosynthesis in general is a key biological process on Earth and Photo system II (PSII) is an important component of this process. PSII is the only enzyme capable of oxidizing water and is largely responsible for the primordial build-up and present maintenance of the oxygen in the atmosphere. This thesis endeavoured to understand the link between structure and function in PSII with special focus on primary photochemistry, repair/photodamage and spectral characteristics. The deletion of the PsbU subunit ofPSII in cyanobacteria caused a decoupling of the Phycobilisomes (PBS) from PSII, likely as a result of increased rates of PSII photodamage with the PBS decoupling acting as a measure to protect PSII from further damage. Isolated fractions of spinach thylakoid membranes were utilized to characterize the heterogeneity present in the various compartments of the thylakoid membrane. It was found that the pooled PSIILHCII pigment populations were connected in the grana stack and there was also a progressive decrease in the reaction rates of primary photochemistry and antennae size of PSII as the sample origin moved from grana to stroma. The results were consistent with PSII complexes becoming damaged in the grana and being sent to the stroma for repair. The dramatic quenching of variable fluorescence and overall fluorescent yield of PSII in desiccated lichens was also studied in order to investigate the mechanism by which the quenching operated. It was determined that the source of the quenching was a novel long wavelength emitting external quencher. Point mutations to amino acids acting as ligands to chromophores of interest in PSII were utilized in cyanobacteria to determine the role of specific chromophores in energy transfer and primary photochemistry. These results indicated that the Hl14 ligated chlorophyll acts as the 'trap' chlorophyll in CP47 at low temperature and that the Q130E mutation imparts considerable changes to PSII electron transfer kinetics, essentially protecting the complex via increased non-radiative charge.

Entering Youthwork Through Love's Many Pathways: A Poetic Rendition

Entering Youth work Through Love's Many Pathways is a text that wanders and digresses to places where, through poetic inquiry and a Spinozist and Sufi framework, the concepts of immanence, love and becoming can be explored. This thesis is framed as a walk through which the researcher / youth worker along with the reader, traverses through five pathways that she considers necessary in cultivating a meaningful relationship with the youth: opening, strength, listening, trust and unconditional compassion. By means of engaging the “self”, this thesis approaches youth work as a field that is relational and socially interconnected. In this sense, this poetic inquiry seeks to rupture predictable patterns of behaviour. One of the ways I do this is through found poetry. Through this specific form of poetic inquiry, I bring together various voices, an assemblage – Rumi, Rilke, Whitman, Lalla, Mirabai and Song of Songs – in order to find my voice and by extension, to help the youth find their voice through a human connection that goes beyond colour, race, gender etc. In other words, my aim is to actualize the experiences of becoming youth worker while being in a field of immanence where similarities are understood and differences respected. My hope is that this project may offer an example of understanding, celebration, and engagement of our mutual differences, while still being able to relate to one another through the many pathways of love.

Electrophysiological constituents of the P100 and N170 ERP complex: De-constructing of face processing using independent component analysis and robust estimation.

The initial timing of face-specific effects in event-related potentials (ERPs) is a point of contention in face processing research. Although effects during the time of the N170 are robust in the literature, inconsistent effects during the time of the P100 challenge the interpretation of the N170 as being the initial face-specific ERP effect. The interpretation of the early P100 effects are often attributed to low-level differences between face stimuli and a host of other image categories. Research using sophisticated controls for low-level stimulus characteristics (Rousselet, Husk, Bennett, & Sekuler, 2008) report robust face effects starting at around 130 ms following stimulus onset. The present study examines the independent components (ICs) of the P100 and N170 complex in the context of a minimally controlled low-level stimulus set and a clear P100 effect for faces versus houses at the scalp. Results indicate that four ICs account for the ERPs to faces and houses in the first 200ms following stimulus onset. The IC that accounts for the majority of the scalp N170 (icNla) begins dissociating stimulus conditions at approximately 130 ms, closely replicating the scalp results of Rousselet et al. (2008). The scalp effects at the time of the P100 are accounted for by two constituent ICs (icP1a and icP1b). The IC that projects the greatest voltage at the scalp during the P100 (icP1a) shows a face-minus-house effect over the period of the P100 that is less robust than the N 170 effect of icN 1 a when measured as the average of single subject differential activation robustness. The second constituent process of the P100 (icP1b), although projecting a smaller voltage to the scalp than icP1a, shows a more robust effect for the face-minus-house contrast starting prior to 100 ms following stimulus onset. Further, the effect expressed by icP1 b takes the form of a larger negative projection to medial occipital sites for houses over faces partially canceling the larger projection of icP1a, thereby enhancing the face positivity at this time. These findings have three main implications for ERP research on face processing: First, the ICs that constitute the face-minus-house P100 effect are independent from the ICs that constitute the N170 effect. This suggests that the P100 effect and the N170 effect are anatomically independent. Second, the timing of the N170 effect can be recovered from scalp ERPs that have spatio-temporally overlapping effects possibly associated with low-level stimulus characteristics. This unmixing of the EEG signals may reduce the need for highly constrained stimulus sets, a characteristic that is not always desirable for a topic that is highly coupled to ecological validity. Third, by unmixing the constituent processes of the EEG signals new analysis strategies are made available. In particular the exploration of the relationship between cortical processes over the period of the P100 and N170 ERP complex (and beyond) may provide previously unaccessible answers to questions such as: Is the face effect a special relationship between low-level and high-level processes along the visual stream?

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.

Heuristics for the Critical Node Detection Problem in Large Complex Networks

Complex networks have recently attracted a significant amount of research attention due to their ability to model real world phenomena. One important problem often encountered is to limit diffusive processes spread over the network, for example mitigating pandemic disease or computer virus spread. A number of problem formulations have been proposed that aim to solve such problems based on desired network characteristics, such as maintaining the largest network component after node removal. The recently formulated critical node detection problem aims to remove a small subset of vertices from the network such that the residual network has minimum pairwise connectivity. Unfortunately, the problem is NP-hard and also the number of constraints is cubic in number of vertices, making very large scale problems impossible to solve with traditional mathematical programming techniques. Even many approximation algorithm strategies such as dynamic programming, evolutionary algorithms, etc. all are unusable for networks that contain thousands to millions of vertices. A computationally efficient and simple approach is required in such circumstances, but none currently exist. In this thesis, such an algorithm is proposed. The methodology is based on a depth-first search traversal of the network, and a specially designed ranking function that considers information local to each vertex. Due to the variety of network structures, a number of characteristics must be taken into consideration and combined into a single rank that measures the utility of removing each vertex. Since removing a vertex in sequential fashion impacts the network structure, an efficient post-processing algorithm is also proposed to quickly re-rank vertices. Experiments on a range of common complex network models with varying number of vertices are considered, in addition to real world networks. The proposed algorithm, DFSH, is shown to be highly competitive and often outperforms existing strategies such as Google PageRank for minimizing pairwise connectivity.

Canadianness is Wilderness? Violent Love Relationships with ‘Wild’ Bodies

This thesis reveals contradictions that Canadians experience with groups attached to western construction of wilderness namely Indigenous people and wildlife. My study analyzes how the discourse of Canadian wilderness identity is played out in Algonquin Provincial Park and Bruce Peninsula National Park in comparison to non-nature/urban spaces (Greater Toronto Area). My investigation employs a critical discourse analysis and participant observation. I undertake three main tasks: 1) I describe how violent love is a dominant discourse at the Parks, 2) I examine evidence of animals and Indigenous people being produced relationally in the Parks, and 3) I analyze how relationships are spatially organized. My research reveals that the Parks conceal practices of violence that are central to the intersections of speciesism and colonialism. I demonstrate how violent love operates across a continuum that is influenced by spatial belonging and distance. This research is a contribution to the production of non-speciesist knowledge.

Mindfulness: An Ancient Wisdom for the Reconceptualisation of Modern Education in the Complex World

Exploring the new science of emergence allows us to create a very different classroom than how the modern classroom has been conceptualised under the mentality of efficiency and output. Working on the whole person, and not just the mind, we see a shift from the epistemic pillars of truth to more ontological concerns as regards student achievement in our post-Modern and critical discourses. It is important to understand these shifts and how we are to transition our own perception and mentality not only in our research methodologies but also our approach to conceptualisations of issues in education and sustainability. We can no longer think linearly to approach complex problems or advocate for education and disregard our interconnectedness insofar as it enhances our children’s education. We must, therefore, contemplate and transition to a world that is ecological and not mechanical, complex and not complicated—in essence, we must work to link mind-body with self-environment and transcend these in order to bring about an integration toward a sustainable future. A fundamental shift in consciousness and perception may implicate our nature of creating dichotomous entities in our own microcosms, yet postmodern theorists assume, a priori, that these dualities can be bridged in naturalism alone. I, on the other hand, embrace metaphysics to understand the implicated modern classroom in a hierarchical context and ask: is not the very omission of metaphysics in postmodern discourse a symptom from an education whose foundation was built in its absence? The very dereliction of ancient wisdom in education is very peculiar indeed. Western mindfulness may play a vital component in consummating pragmatic idealism, but only under circumstances admitting metaphysics can we truly transcend our limitations, thereby placing Eastern Mindfulness not as an ecological component, but as an ecological and metaphysical foundation.

Object-Oriented Genetic Programming for the Automatic Inference of Graph Models for Complex Networks

Complex networks are systems of entities that are interconnected through meaningful relationships. The result of the relations between entities forms a structure that has a statistical complexity that is not formed by random chance. In the study of complex networks, many graph models have been proposed to model the behaviours observed. However, constructing graph models manually is tedious and problematic. Many of the models proposed in the literature have been cited as having inaccuracies with respect to the complex networks they represent. However, recently, an approach that automates the inference of graph models was proposed by Bailey [10] The proposed methodology employs genetic programming (GP) to produce graph models that approximate various properties of an exemplary graph of a targeted complex network. However, there is a great deal already known about complex networks, in general, and often specific knowledge is held about the network being modelled. The knowledge, albeit incomplete, is important in constructing a graph model. However it is difficult to incorporate such knowledge using existing GP techniques. Thus, this thesis proposes a novel GP system which can incorporate incomplete expert knowledge that assists in the evolution of a graph model. Inspired by existing graph models, an abstract graph model was developed to serve as an embryo for inferring graph models of some complex networks. The GP system and abstract model were used to reproduce well-known graph models. The results indicated that the system was able to evolve models that produced networks that had structural similarities to the networks generated by the respective target models.