Environmental variables and multivariate seabed classification maps via k means clustering of Potter Cove, Antarctica, link to input and result files in GeoTIFF format

This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

New Techniques in Deep Representation Learning

Thesis (Ph.D.)--University of Washington, 2016-06

Optimized Decoding for Auditory Attention Detection

Thesis (Master's)--University of Washington, 2016-06

Personality disorders and adult attachment dimensions in a mixed psychiatric sample: A multivariate study

The associations between personality disorders and adult attachment dimensions were assessed in a sample of 487 consecutively admitted psychiatric subjects. Canonical correlation analysis showed that two sets of moderately correlated canonical variates explained the correlations between personality disorders and adult attachment patterns. The first and second attachment variates closely resembled the avoidance and anxiety attachment dimensions, respectively. The first personality disorder variate was mainly characterized by avoidant, depressive, paranoid, and schizotypal personality disorders, whereas dependent, histrionic, and borderline personality disorders loaded on the second canonical variate. However, these linear combinations of personality disorders were different from those obtained from principal component analysis. The results extend previous studies linking personality disorders and attachment patterns and suggest the importance of focusing on specific constellations of symptoms associated with dimensions of insecurity.

Power perceptions and modes of complaining in higher education

This study examines the relationship between student perceptions of different types of educator power and different modes of student complaining behaviour in the case of university education. A large sample of marketing students in the business school responded to the study from a state university in Northeastern United States. Factor analysis and canonical correlation analysis are used to explore the relationships between five bases of power perceptions (referent, expert, reward, legitimate, and punishment) and four modes of complaining behaviour (voice, negative word of mouth, third party, and exit). The results indicate that students engage in different modes of complaining as they perceive different types of educator power. The predominant complaining mode is found to be voice under referent or expert power, third party under legitimate power, and exit under reward or punishment power. Our findings offer important implications for student satisfaction, retention, and completion rates in higher education.

The relationship of spirituality and the health promoting behaviors of diet and exercise of African -American women

Public health data show that African-Americans have not adopted health-promoting behaviors of diet and exercise. Spirituality, important in the lives of many African-American women, may be associated with health-promoting behaviors. This study was designed to determine how spirituality relates to health-promoting behaviors in African-American women. Burkhardt's theoretical framework for spirituality was adopted and measures were selected for the three elements of the framework: connectedness with self, others, and environment. ^ The study used a descriptive cross sectional correlational design to investigate the relationships of the independent variables of spirituality, sociodemographics, and BMI, to the dependent variables of diet and exercise, to answer the two primary questions: What is the role of spirituality in impacting the health-promoting behaviors of African-American women? Of the independent variables of spirituality, sociodemographics, and BMI, which are the best predictors of diet and exercise? ^ Central and South Floridian African-American women (n = 260) between 18 and 82 years of age completed several questionnaires: Rosenberg's Self-Esteem Scale, Health Promoting Lifestyle Profile II, Spiritual Perspective Scale, Brief Block Food Frequency, and socio-demographic information. ^ Hierarchical regression identified 40% of the variability of diet to be explained by socio-demographic (education) and spirituality variables (stress management and health responsibility) (p < .001). Twenty-nine percent of the variability of exercise was explained by socio-demographic (education) and spirituality variables (stress management) (p < .001). Canonical correlation analysis identified a significant pair of canonical variates which indicated individuals with good nutrition (.95), increased physical activity (.79), and healthy eating (.42) also had better stress management (.88), better health responsibility (.67), higher spiritual growth (.66), better interpersonal relations (.50), more education (.49), and higher self-esteem (.33). The set explained 57% of the variability (p < .001). ^ An understanding of the factors that influence these women's decision to utilize health-promoting strategies could provide health professionals with additional information to enable them to design culturally and spiritually related health messages for African-American women. The findings of this present study speak of the importance of focusing on stress management, health responsibility, spiritual growth, interpersonal relations and self-esteem along with diet and exercise; this will likely provide improvement in the health-promoting behaviors of African-American women. ^

POTENCIAL DA ASSOCIAÇÃO Pisolithus microcarpus COM MUDAS DE Corymbia citriodora EM SOLO CONTAMINADO COM ZINCO

O uso de plantas com potencial de associação com microrganismos é uma prática frequente em solos contaminados por metais pesados, considerada de baixo custo e ambientalmente correta. O trabalho objetivou avaliar o crescimento do Corymbia citriodora (Hook.) K.D. Hill & L.A.S. Johnson e o efeito da inoculação com Pisolithus microcarpus UFSC-Pt116 em solo contaminado com Zn. O delineamento experimental foi inteiramente casualizado em arranjo fatorial (2 x 6), sendo com e sem inóculo e seis doses de Zn (0, 300, 600, 900, 1200 e 1500 mg kg-1 de solo), com seis repetições. As mudas foram inoculadas e cultivadas durante 90 dias em viveiro. Após 67 dias do transplante definitivo foi avaliado o percentual de colonização ectomicorrízica, a altura de planta, diâmetro do colo, número de folhas, índice de clorofila total, volume radicular, massa seca das folhas, da haste caulinar, radicular e total, relação massa seca aérea/massa seca radicular e a relação altura/diâmetro do colo. O percentual de colonização ectomicorrízica em Corymbia citriodora é estimulado pelo acréscimo de até 1412,21 mg kg-1 de Zn no solo. O Corymbia citriodora é tolerante a adição de até 1500 mg kg-1 de zinco em solo com 81% de argila, mesmo sem a inoculação com Pisolithus microcarpus. A análise de correlação canônica evidencia que a inoculação com P. microcarpus favorece a massa seca total, radicular e da parte aérea de Corymbia citriodora cultivado em solo com 81% de argila contaminada com 600 mg kg-1 de Zn.

Análise de correlação canónica : extensões e aplicações

Neste trabalho apresentamos a teoria da análise de correlação canónica, uma técnica de análise estatística multivariada para o estudo da relação, simultânea, entre dois, três ou mais grupos de variáveis. Descrevemos a natureza da correlação canónica com três ou mais variáveis, com modelos matemáticos, fazendo uma síntese dos métodos de generalização de correlação canónica nomeadamente o método Ssqcor, método Sumcor, método Ecart, método Maxvar, método Minvar, e o método de Carroll. Apresentamos uma aplicação utilizando dados provenientes do cálculo do Índice de Preços no Consumidor IPC, produzido pelo INE - STP (Instituto Nacional de Estatística de São Tomé e Príncipe), referente ao período 2010 a 2014. Estamos interessados em conhecer as correlações canónicas entre grupos de variáveis relacionadas com o cabaz de produtos pré-estabelecido para o cálculo do índice de preços no consumidor, concretamente os produtos alimentares (PA), produtos para bebidas (PB) e produtos não alimentares (PNA), constituindo assim os três grandes grupos de variáveis da nossa pesquisa.

Principal components and generalized linear modeling in the correlation between hospital admissions and air pollution

OBJECTIVE To analyze the association between concentrations of air pollutants and admissions for respiratory causes in children. METHODS Ecological time series study. Daily figures for hospital admissions of children aged < 6, and daily concentrations of air pollutants (PM10, SO2, NO2, O3 and CO) were analyzed in the Região da Grande Vitória, ES, Southeastern Brazil, from January 2005 to December 2010. For statistical analysis, two techniques were combined: Poisson regression with generalized additive models and principal model component analysis. Those analysis techniques complemented each other and provided more significant estimates in the estimation of relative risk. The models were adjusted for temporal trend, seasonality, day of the week, meteorological factors and autocorrelation. In the final adjustment of the model, it was necessary to include models of the Autoregressive Moving Average Models (p, q) type in the residuals in order to eliminate the autocorrelation structures present in the components. RESULTS For every 10:49 μg/m3 increase (interquartile range) in levels of the pollutant PM10 there was a 3.0% increase in the relative risk estimated using the generalized additive model analysis of main components-seasonal autoregressive – while in the usual generalized additive model, the estimate was 2.0%. CONCLUSIONS Compared to the usual generalized additive model, in general, the proposed aspect of generalized additive model − principal component analysis, showed better results in estimating relative risk and quality of fit.

Event-related FMRI analysis with maximum correlation modelling

Functional magnetic resonance imaging (FMRI) analysis methods can be quite generally divided into hypothesis-driven and data-driven approaches. The former are utilised in the majority of FMRI studies, where a specific haemodynamic response is modelled utilising knowledge of event timing during the scan, and is tested against the data using a t test or a correlation analysis. These approaches often lack the flexibility to account for variability in haemodynamic response across subjects and brain regions which is of specific interest in high-temporal resolution event-related studies. Current data-driven approaches attempt to identify components of interest in the data, but currently do not utilise any physiological information for the discrimination of these components. Here we present a hypothesis-driven approach that is an extension of Friman's maximum correlation modelling method (Neurolmage 16, 454-464, 2002) specifically focused on discriminating the temporal characteristics of event-related haemodynamic activity. Test analyses, on both simulated and real event-related FMRI data, will be presented.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Tying up the loose ends in simple correspondence analysis

Although correspondence analysis is now widely available in statistical software packages and applied in a variety of contexts, notably the social and environmental sciences, there are still some misconceptions about this method as well as unresolved issues which remain controversial to this day. In this paper we hope to settle these matters, namely (i) the way CA measures variance in a two-way table and how to compare variances between tables of different sizes, (ii) the influence, or rather lack of influence, of outliers in the usual CA maps, (iii) the scaling issue and the biplot interpretation of maps,(iv) whether or not to rotate a solution, and (v) statistical significance of results.

Correspondence analysis and categorical conjoint measurement

We show the equivalence between the use of correspondence analysis (CA)of concadenated tables and the application of a particular version ofconjoint analysis called categorical conjoint measurement (CCM). Theconnection is established using canonical correlation (CC). The second part introduces the interaction e¤ects in all three variants of theanalysis and shows how to pass between the results of each analysis.

(Appendix) Analysis of benthic foraminifera from ODP Leg 181 and DSDP Leg 90

Canonical correspondence analysis indicates that the distribution of Neogene benthic foraminiferal faunas (>63 µm) in seven DSDP and ODP sites (500-4500 m water depth) east of New Zealand (38-51°S, 170°E-170°W) is most strongly influenced by depth (water mass stratification), and secondly by age (palaeoceanographic changes influencing faunal composition and biotic evolution). Stratigraphic faunal changes are interpretted in terms of the pulsed sequential development of southern, and later northern, polar glaciation and consequent cooling of bottom waters, increased vertical and lateral stratification of ocean water masses, and increased overall and seasonal surface water productivity. Oligocene initiation of the Antarctic Circumpolar Current and Deep Western Boundary Current (DWBC), flowing northwards past New Zealand, resulted in extensive hiatuses throughout the Southwest Pacific, some extending through into the Miocene. Planktic foraminiferal fragmentation index values indicate that carbonate dissolution was significant at abyssal depths throughout most of the Neogene, peaking at upper abyssal depths in the late Miocene (11-7 Ma), with the lysocline progressively deepened thereafter. Miocene abyssal faunas are dominated by Globocassidulina subglobosa and Oridorsalis umbonatus, with increasing Epistominella exigua after 16 Ma at upper abyssal depths. Peak abundances of Epistominella umbonifera indicate increased input of cold Southern Component Water to the DWBC at 7-6 Ma. Faunal association changes imply establishment of the modern Oxygen Minimum Zone (upper Circumpolar Deep Water) in the latest Miocene. Significant latitudinal differences between the benthic foraminiferal faunas at lower bathyal depths indicate the existence of an oceanic front along the Chatham Rise (location of present Subtropical Front), since the early late Miocene at least, with more pulsed productivity (higher E. exigua) along the south side. Modern Antarctic Intermediate Water faunal associations were established north of the Chatham Rise at 10-9 Ma, and south of it at 3-1.5 Ma. Middle-upper bathyal faunas on the Campbell Plateau are dominated by reticulate bolivinids during the early and middle Miocene, indicative of sustained productivity above relatively sluggish, suboxic bottom waters. Faunal changes and hiatuses indicate increased current vigour over the Campbell Plateau from the latest Miocene on. Surface water productivity (food supply) appears to have increased in three steps (at times of enhanced global cooling) marked by substantially increased relative abundance of: (1) Abditodentrix pseudothalmanni, Alabaminella weddellensis, Cassidulina norvangi (16-15 Ma, increased pulsed productivity); (2) Bulimina marginata f. aculeata, Nonionella auris, Trifarina angulosa, Uvigerina peregrina (3-1.5 Ma, increased overall productivity); and (3) Cassidulina carinata (1-0.5 Ma, increased overall productivity). Three intervals of deep-sea benthic foraminiferal taxonomic turnover are recognised (16-15, 11.5-10, 2-0.5 Ma) corresponding to intervals of enhanced global cooling and possible productivity changes. The late Pliocene-middle Pleistocene extinction, associated with increasing Northern Hemisphere glaciation, culminating in the middle Pleistocene climatic transition, was more significant in the study area than the earlier Neogene turnovers.