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Thesis studied correlations between swallowing accelerometry parameters and anthropometrics in 50 healthy participants. Anthropometrics include: age, gender, weight, height, body fat percent, neck circumference and mandibular length. Dual-axis swallowing signals, from a biaxial accelerometer were obtained for 5-saliva and 10-water (5-wet and 5-wet chin-tuck) swallows per participant. Two patient-independent automatic segmentation algorithms using discrete wavelet transforms of swallowing sequences segmented: 1) saliva/wet swallows and 2) wet chin-tuck swallows. Extraction of swallows hinged on dynamic thresholding based on signal statistics. Canonical correlation analysis was performed on sets of anthropometric and swallowing signal variables including: variance, skewness, kurtosis, autocorrelation decay time, energy, scale and peak-amplitude. For wet swallows, significant linear relationships were found between signal and anthropometric variables. In superior-inferior directions, correlations linked weight, age and gender to skewness and signal-memory. In anterior-posterior directions, age was correlated with kurtosis and signal-memory. No significant relationship was observed for dry and wet chin-tuck swallowing

Thesis (Ph.D.)--University of Melbourne, Dept. of Mathematics and Statistics, 2007. / Typescript. Includes bibliographical references.

The present dissertation consists of four interconnected projects. In the first, we introduce and study what we call factorizable module algebras. These are $U_q(\mathfrak{g})$-module algebras $A$ which factor, potentially after localization, as the tensor product of the subalgebra $A^+$ of highest weight vectors of $A$ and a copy of the quantum coordinate algebra $\mathcal{A}_q[U]$, where $U$ is a maximal unipotent subgroup of $G$, a semisimple Lie group whose Lie algebra is $\mathfrak{g}$. The class of factorizable module algebras is surprisingly rich, in particular including the quantum coordinate algebras $\mathcal{A}_q[Mat_{m,n}]$, $\mathcal{A}_q[G]$ and $\mathcal{A}_q[G/U]$. It is closed under the braided tensor product and, moreover, the subalgebra $A^+$ of each such $A$ is naturally a module algebra over the quantization of $\mathfrak{g}^*$, the Lie algebra of the Poisson dual group $G^*$. The aforementioned examples of factorizable module algebras all possess dual canonical bases which behave nicely with respect to factorization $A=A^+\otimes \mathcal{A}_q[U]$. We expect the same is true for many other members of this class, including braided tensor products of such. To facilitate such a construction in tensor products, we propose an axiomatic framework of based modules which, in particular, vastly generalizes Lusztig's notion of based modules. We argue that all of the aforementioned $U_q(\mathfrak{g})$-module algebras (and many others) with their dual canonical bases are included, along with their tensor products. One of the central objects of study emerging from our generalization of Lusztig's based modules is a new (very canonical) basis $\mathcal{B}^{\diamond n}$ in the $n$-th braided tensor power $\mathcal{A}_q[G/U]$. We argue (yet conjecturally) that $\mathcal{A}_q[G/U]^{\underline{\otimes}n}$ has a quantum cluster structure and conjecture that the expected cluster structure structure on $\mathcal{A}_q[G/U]^{\underline{\otimes}n}$ is completely controlled by the real elements of our canonical basis $\mathcal{B}^{\diamond n}$. Finally, in order to partially explain the monoidal structures appearing above, we provide an axiomatic framework to construct examples of bialgebroids of Sweedler type. In particular, we describe a bialgebroid structure on $\mathfrak{u}_q(\mathfrak{g})\rtimes\mathbb{Q} C_2$, where $\mathfrak{u}_q(\mathfrak{g})$ is the small quantum group and $C_2$ is the cyclic group of order two. This dissertation contains previously published co-authored material.

M.A. (Afrikaans) / A comparison between the narrative-fictive discourse situation and the canonical discourse situation reveals differences as well as similarities between the two modes of discourse. Every act of utterance occurs in a spatio-temporal context whose centre or zero point coincides with the speaker's here and now. The literary discourse is conducted on more than one level and this introduces more than one context into the universe of discourse. The existence of two contexts has marked implications for the use of deictic terms in the narrative text. In the first chapter of this study the deictic categories of person, time and place in the canonical situation-of-utterance is placed alongside the same categories in the narrative-fictive discourse situation. It is established that a primary as well as a fictive deictic centre exists in the latter. The second chapter deals with the structural function of the deictic categories in the narrative text of Die kremetartekspedisie. There is a continual shift between the narrating-self (the origo of the primary deictic centre) and the experiencing-self (origo of the fictive deictic centre). The pronominal reference remains in the first person and it is at the spatio-temporal level that the shift between the two selves is effected...

Recently there has been a renewed interest in formative measurement and its role in properly specified models. Formative measurement models are difficult to identify, and hence to estimate and test. Existing solutions to the identification problem are shown to not adequately represent the formative constructs of interest. We propose a new two-step approach to operationalize a formatively measured construct that allows a closely matched common factor equivalent to be included in any structural equation model. We provide an artificial example and an original empirical study of privacy to illustrate our approach. Detailed proofs are given in an appendix.

archives@tulane.edu / Modern biomedical studies often collect multiple types of high-dimensional data on a common set of objects. A representative model for the integrative analysis of multiple data types is to decompose each data matrix into a low-rank common-source matrix generated by latent factors shared across all data types, a low-rank distinctive-source matrix corresponding to each data type, and an additive noise matrix. We propose a novel decomposition method, called the decomposition-based generalized canonical correlation analysis, which appropriately defines those matrices by imposing a desirable orthogonality constraint on distinctive latent factors that aims to sufficiently capture the common latent factors. To further delineate the common and distinctive patterns between two data types, we propose another new decomposition method, called the common and distinctive pattern analysis. This method takes into account the common and distinctive information between the coefficient matrices of the common latent factors. We develop consistent estimation approaches for both proposed decompositions under high-dimensional settings, and demonstrate their finite-sample performance via extensive simulations. We illustrate the superiority of proposed methods over the state of the arts by real-world data examples obtained from The Cancer Genome Atlas and Human Connectome Project. / 1 / Zhe Qu

京都大学 / 0048 / 新制・課程博士 / 博士(理学) / 甲第21533号 / 理博第4440号 / 新制||理||1638(附属図書館) / 京都大学大学院理学研究科数学・数理解析専攻 / (主査)教授 並河 良典, 教授 森脇 淳, 教授 吉川 謙一 / 学位規則第4条第1項該当 / Doctor of Science / Kyoto University / DGAM

Understanding how communication between brain areas evolves to support dynamic function remains a fundamental challenge in neuroscience. One approach to this question is functional connectivity analysis, in which statistical coupling measures are employed to detect signatures of interactions between brain regions. Because the brain uses multiple communication mechanisms at different temporal and spatial scales, and because the neuronal signatures of communication are often weak, powerful connectivity inference methodologies require continued development specific to these challenges. Here we address the challenge of inferring task-related functional connectivity in brain voltage recordings. We first develop a framework for detecting changes in statistical coupling that occur reliably in a task relative to a baseline period. The framework characterizes the dynamics of connectivity changes, allows inference on multiple spatial scales, and assesses statistical uncertainty. This general framework is modular and applicable to a wide range of tasks and research questions. We demonstrate the flexibility of the framework in the second part of this thesis, in which we refine the coupling statistics and hypothesis tests to improve statistical power and test different proposed connectivity mechanisms. In particular, we introduce frequency domain coupling measures and define test statistics that exploit theoretical properties and capture known sampling variability. The resulting test statistics use correlation, coherence, canonical correlation, and canonical coherence to infer task-related changes in coupling. Because canonical correlation and canonical coherence are not commonly used in functional connectivity analyses, we derive the theoretical values and statistical estimators for these measures. In the third part of this thesis, we present a sample application of these techniques to electrocorticography data collected during an overt reading task. We discuss the challenges that arise with task-related human data, which is often noisy and underpowered, and present functional connectivity results in the context of traditional and contemporary within-electrode analytics. In two of nine subjects we observe time-domain and frequency-domain network changes that accord with theoretical models of information routing during motor processing. Taken together, this work contributes a methodological framework for inferring task-related functional connectivity across spatial and temporal scales, and supports insight into the rapid, dynamic functional coupling of human speech.

This article reports on the results of a survey which investigated the nature of relationships between hospital and multihospital organization-centered factors and background characteristics, and multihospital organization effectiveness. Canonical correlation is employed in analyzing the data. Results and their implications are discussed.