Reality status evaluations in mediated experiences /

This paper explores the cognitive functions of the Reality Status Evaluation (RSE) system in our experiences of narrative mediated messages (NMM) (fictional, narrative, audio-visual one-way input and moving picture messages), such as fictional TV programs and films. We regard reality in mediated experiences as a special mental and emotional construction and a multi-dimensional concept. We argue that viewers' reality sense in NMM is influenced by many factors with "real - on" as the default value. Some of these factors function as primary mental processes, including the content realism factors of those messages such as Factuality (F), Social Realism (SR), Life Relevance (LR), and Perceptual Realism - involvement (PR), which would have direct impacts on reality evaluations. Other factors, such as Narrative Meaning (NM), Emotional Responses, and personality trait Absorption (AB), will influence the reality evaluations directly or through the mediations of these main dimensions. I designed a questionnaire to study this theoretical construction. I developed items to form scales and sub-scales measuring viewers' subjective experiences of reality evaluations and these factors. Pertinent statistical techniques, such as internal consistency and factorial analysis, were employed to make revisions and improve the quality of the questionnaire. In the formal experiment, after viewing two short films, which were selected as high or low narrative structure messages from previous experiments, participants were required to answer the questionnaire, Absorption questionnaire, and SAM (Self-Assessment Manikin, measuring immediate emotional responses). Results were analyzed using the EQS, structural equation modeling (SEM), and discussed in terms oflatent relations among these subjective factors in mediated experience. The present results supported most of my theoretical hypotheses. In NMM, three main jactors, or dimensions, could be extracted in viewers' subjective reality evaluations: Social Realism (combining with Factuality), Life Relevance and Perceptual Realism. I designed two ways to assess viewers' understanding of na"ative meanings in mediated messages, questionnaire (NM-Q) and rating (NM-R) measurement, and its significant influences on reality evaluations was supported in the final EQS models. Particularly in high story stnlcture messages, the effect of Narrative Meaning (NM) can rarely be explained by only these dimensions of reality evaluations. Also, Empathy seems to playa more important role in RSE of low story structure messages. Also, I focused on two other factors that were pertinent to RSE in NMM, the personality trait Absorption, and Emotional Responses (including two dimensions: Valence and Intensity). Final model results partly supported my theoretical hypotheses about the relationships among Absorption (AB), Social Realism (SR) and Life Relevance (LR); and the immediate impact of Emotional Responses on Perceptual Realism cPR).

Hyperspectral Mineral Identification using SVM and SOM

Remote sensing techniques involving hyperspectral imagery have applications in a number of sciences that study some aspects of the surface of the planet. The analysis of hyperspectral images is complex because of the large amount of information involved and the noise within that data. Investigating images with regard to identify minerals, rocks, vegetation and other materials is an application of hyperspectral remote sensing in the earth sciences. This thesis evaluates the performance of two classification and clustering techniques on hyperspectral images for mineral identification. Support Vector Machines (SVM) and Self-Organizing Maps (SOM) are applied as classification and clustering techniques, respectively. Principal Component Analysis (PCA) is used to prepare the data to be analyzed. The purpose of using PCA is to reduce the amount of data that needs to be processed by identifying the most important components within the data. A well-studied dataset from Cuprite, Nevada and a dataset of more complex data from Baffin Island were used to assess the performance of these techniques. The main goal of this research study is to evaluate the advantage of training a classifier based on a small amount of data compared to an unsupervised method. Determining the effect of feature extraction on the accuracy of the clustering and classification method is another goal of this research. This thesis concludes that using PCA increases the learning accuracy, and especially so in classification. SVM classifies Cuprite data with a high precision and the SOM challenges SVM on datasets with high level of noise (like Baffin Island).

Role of Phosphorylation of the Oxysterol Binding Protein (OSBP) in (PI(4)P) and Sterol-Containing Membrane Recognition and Binding

Studies have demonstrated that the oxysterol binding protein (OSBP) acts as a phosphatidylinositol phosphate (PIP)-sterol exchanger at membrane contact sites (MCS) of the endoplasmic reticulum (ER) and Golgi. OSBP is known to pick up phosphatidylinositol-4-phosphate (PI(4)P) from the ER, transfer it to the trans-Golgi in exchange for a cholesterol molecule that is then transferred from the trans-Golgi to the ER. Upon further examination of this pathway by Ridgway et al. (1), it appeared that phosphorylation of OSBP played a role in the localization of OSBP. The dephosphorylation state of OSBP was linked to Golgi localization and the depletion of cholesterol at the ER. To mimic the phosphorylated state of OSBP, the mutant OSBP-S5E was designed by Ridgway et al. (1). The lipid and sterol recognition by wt-OSBP and its phosphomimic mutant OSBP-S5E were investigated using immobilized lipid bilayers and dual polarization interferometry (DPI). DPI is a technique in which the protein binding affinity to immobilized lipid bilayers is measured and the binding behavior is examined through real time. Lipid bilayers containing 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC) and varying concentrations of PI(4)Ps or sterols (cholesterol or 25-hydroxycholesterol) were immobilized on a silicon nitride chip. It was determined that wt-OSBP binds differently to PI(4)P-containing bilayers compared to OSBP-S5E. The binding behavior suggested that wt-OSBP extracts PI(4)P and the change in the binding behavior, in the case of OSBP-S5E, suggested that the phosphorylation of OSBP may prevent the recognition and/or extraction of PI(4)P. In the presence of sterols, the overall binding behavior of OSBP, regardless of phosphorylation state, was fairly similar. The maximum specific bound mass of OSBP to sterols did not differ as the concentration of sterols increased. However, comparing the maximum specific bound mass of OSBP to cholesterol with oxysterol (25-hydroxycholesterol), OSBP displayed nearly a 2-fold increase in bound mass. With the absence of the wt-OSBP-PI(4)P binding behavior, it can be speculated that the sterols were not extracted. In addition, the binding behavior of OSBP was further tested using a fluorescence based binding assay. Using 22-(N-(7-nitrobenz-2-oxa-1,3-diazol-4-yl)amino)-23,24-bisnor-5-cholen-3β-ol (22-NBD cholesterol), wt-OSBP a one site binding dissociation constant Kd, of 15 ± 1.4 nM was determined. OSBP-S5E did not bind to 22-NBD cholesterol and Kd value was not obtained.

What happens in the first 200 ms of word reading : ERP studies on visual word recognition with top-down and bottom-up approaches /

In this thesis, three main questions were addressed using event-related potentials (ERPs): (1) the timing of lexical semantic access, (2) the influence of "top-down" processes on visual word processing, and (3) the influence of "bottom-up" factors on visual word processing. The timing of lexical semantic access was investigated in two studies using different designs. In Study 1,14 participants completed two tasks: a standard lexical decision (LD) task which required a word/nonword decision to each target stimulus, and a semantically primed version (LS) of it using the same category of words (e.g., animal) within each block following which participants made a category judgment. In Study 2, another 12 participants performed a standard semantic priming task, where target stimulus words (e.g., nurse) could be either semantically related or unrelated to their primes (e.g., doctor, tree) but the order of presentation was randomized. We found evidence in both ERP studies that lexical semantic access might occur early within the first 200 ms (at about 170 ms for Study 1 and at about 160 ms for Study 2). Our results were consistent with more recent ERP and eye-tracking studies and are in contrast with the traditional research focus on the N400 component. "Top-down" processes, such as a person's expectation and strategic decisions, were possible in Study 1 because of the blocked design, but they were not for Study 2 with a randomized design. Comparing results from two studies, we found that visual word processing could be affected by a person's expectation and the effect occurred early at a sensory/perceptual stage: a semantic task effect in the PI component at about 100 ms in the ERP was found in Study 1 , but not in Study 2. Furthermore, we found that such "top-down" influence on visual word processing might be mediated through separate mechanisms depending on whether the stimulus was a word or a nonword. "Bottom-up" factors involve inherent characteristics of particular words, such as bigram frequency (the total frequency of two-letter combinations of a word), word frequency (the frequency of the written form of a word), and neighborhood density (the number of words that can be generated by changing one letter of an original word or nonword). A bigram frequency effect was found when comparing the results from Studies 1 and 2, but it was examined more closely in Study 3. Fourteen participants performed a similar standard lexical decision task but the words and nonwords were selected systematically to provide a greater range in the aforementioned factors. As a result, a total of 18 word conditions were created with 18 nonword conditions matched on neighborhood density and neighborhood frequency. Using multiple regression analyses, we foimd that the PI amplitude was significantly related to bigram frequency for both words and nonwords, consistent with results from Studies 1 and 2. In addition, word frequency and neighborhood frequency were also able to influence the PI amplitude separately for words and for nonwords and there appeared to be a spatial dissociation between the two effects: for words, the word frequency effect in PI was found at the left electrode site; for nonwords, the neighborhood frequency effect in PI was fovind at the right elecfrode site. The implications of otir findings are discussed.

Visual word learning in good and poor readers

Forty students from regular, grade five classes were divided into two groups of twenty, a good reader group and a' poor reader group, on the basis. of their reading scores on Canadian Achievement Tests. .The subjects took. part in four experimental conditions iM which they .learned lists of pronounceable and unprono~nceable pseudowords, some with semantic referents, and responded to questions designed tci test visual perceptu~l learning and lexical ·and semantic association learning. It' was hypothesized "that the good reade~ group would be able to make use of graphemic and phonemic redundancy patterns in order to improv~·visuSl perceptual learning and lexical and semantic association lea~ningto a greater extent. than would .the poor reader gr6up. The data supported this hypothesis, and also indicated that, although the poor readers were less adept at using familiar sound and letter patterns, they were more dependent on· such pa~terns as an aid to visual recognition memory and semantic recall than were the good readers. It wa.s postulated that poor readers are in a double- ~ . bind situatio~ of having to choose between using weak graphemic-semantic associations or gr~pheme-phoneme associations which are also weak and which have hindered them in developing automaticity in. reading.

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.