Microbial Interactions in Coupled Climate-Biogeochemical Systems

This thesis addresses time-series analyses of microbial (i.e. marine heterotrophic bacteria and phytoplankton) and microbially relevant ecosystem variables at two ocean time series stations - Palmer Station in the coastal Western Antarctic Peninsula (WAP) and the Bermuda Atlantic Time-series Study (BATS) site in the Sargasso Sea. Using a diverse spectrum of statistical analyses and models, the aim of this thesis is to gain the better insight into 1) variability of microbial and ecosystem processes across varying time scales, from seasonal to interdecadal, and 2) how each process is influenced by variability of surrounding local physical forcing factors as well as regional and global-scale climate variability along the study region. Chapter 1 provides an introduction to the two study sites as well as a brief history of the ocean time-series programs there. Chapter 2 deals with phytoplankton and nutrient drawdown variability over an interdecadal (1993-2013) period using seasonal time-series variables collected at Palmer Station during full 6-months of Austral growing seasons (October-March). Specifically, the linkage between large-scale climate modes relevant to the WAP area and phytoplankton and nutrient patterns is explored to establish the underlying mechanisms of the observed ecosystem variability, which is ultimately triggered by climate conditions via mediatory physical forcing factors. Chapter 3 addresses a decadal (2002-2014) variability of heterotrophic bacterial variables collected at Palmer Station in Antarctica. This Chapter 3 provides an insight into why bacterial activity was shown to be restricted in this very productive ecosystem from diverse aspects gained using different statistical approaches. Furthermore, the linkage between bacterial properties and surrounding environmental conditions is explored. Finally, Chapter 4 concerns an event-scale phenomenon - the frequency of winter storms - and its impact on bacterial dynamics and ecological processes at the BATS site. Using a previously developed storm tracking algorithm, this study benefits from establishing a mechanistic connection between storm forcing and bacterial processes via storm-induced variability of physical environments - the extent of wind-mixing and entrainment of cold water into the upper mixed-layer. The finding of Chapter 4 is novel in the aspect that prevalent negative North Atlantic Oscillation (NAO) conditions, which lead to frequent arrivals of winter storms over the BATS region, in part, explain a significant decreasing bacterial trend over the past 24-year period. Overall, my thesis, in conjunction with work performed by fellow microbial oceanographers, aims to provide evidence of microbial responses to physical forcings across varying time scales in the strongly coupled climate-biogeochemical systems at two contrasting ocean sites based on a variety of statistical approaches

Identity Formation among North Korean Defectors in South Korea: Implications from a Socio-Cultural Learning Theoretical Lens

This paper aims to analyze the present situation of North Korean Defectors (NKDs)’ adaptation in South Korea from the relationship between social adjustment and identity construction. By using a socio-cultural learning theoretical lens, it reveals structural barriers and tacit differentiations to hinder NKDs’ participation and to disturb their identity formation

JMASM 32: SAS Template for Single-Subject Experimental Designs

Meta-analysis has been used to synthesize research findings and to evaluate the effectiveness of treatments or the accuracy of diagnostic tools. Although meta-analytic techniques were developed to synthesize the results of several studies, controversy exists as to how to quantify the results from singlesubject experimental designs (SSEDs). The most commonly used metrics are reviewed, including nonregression and regression based methods. The application of the SAS template is demonstrated through simulated data sets. The SAS templates can be modified to accommodate a more complex data structure

The Social Networks of Korean Female Adult Learners in a Middle School

This study investigates the social networks of Korean female adult learners in middle school through social network analysis and examines the development of these networks by interviewing the main actors involved

The Leading Causes and Consequences of Citizenship Pressure in the Hotel Industry

Purpose – This study aims to examine the causes of citizenship pressure and to investigate the relationship between citizenship pressure, job stress and turnover intentions. Specifically, the current study examines the effects of the personality trait of neuroticism and the organizational cultures of bureaucracy and the market. Design/methodology/approach – Data were collected from 224 hotel employees in the People’s Republic of China using a self-administered survey questionnaire. The participants completed measures examining citizenship pressure, personality, organizational culture, job stress and intention to quit. Structural equation modeling was used to test the research hypotheses. Findings – The results showed that employees who are more neurotic are more likely to experience citizenship pressure. Moreover, citizenship pressure was found to increase job stress and turnover intentions. However, a bureaucratic culture, which prizes stability, was found to reduce citizenship pressure. Practical implications – This study presents factors that may influence hotel employees’ perceptions of citizenship pressure and reveals the negative consequences of such pressure. Thus, the study results contribute to a better understanding of citizenship pressure and can be used to develop guidelines to reduce citizenship pressure in work environments. Originality/value – To the best of the authors’ knowledge, the current study is the first empirical study to examine the antecedents and consequences of citizenship pressure in the hotel industry. Moreover, previous citizenship pressure studies have mainly been conducted in a Western cultural context; it is unclear whether citizenship pressure can be similarly observed in China, where the nature and form of employment relationships differ significantly from those in Western countries

Applications of Machine Learning in Pharmacogenomics: Clustering Plasma Concentration-Time Curves

Pharmaceutical researchers are continually searching for techniques to improve both drug development processes and patient outcomes. An area of recent interest is the potential for machine learning (ML) applications within pharmacology. One such application not yet given close study is the unsupervised clustering of plasma concentration-time curves, hereafter, pharmacokinetic (PK) curves. In this paper, we present our findings on how to cluster PK curves by their similarity. Specifically, we find clustering to be effective at identifying similar-shaped PK curves and informative for understanding patterns within each cluster of PK curves. Because PK curves are time series data objects, our approach utilizes the extensive body of research related to the clustering of time series data as a starting point. As such, we examine many dissimilarity measures between time series data objects to find those most suitable for PK curves. We identify Euclidean distance as generally most appropriate for clustering PK curves, and we further show that dynamic time warping, Fr\'{e}chet, and structure-based measures of dissimilarity like correlation may produce unexpected results. As an illustration, we apply these methods in a case study with 250 PK curves used in a previous pharmacogenomic study. Our case study finds that an unsupervised ML clustering with Euclidean distance, without any subject genetic information, is able to independently validate the same conclusions as the reference pharmacogenomic results. To our knowledge, this is the first such demonstration. Further, the case study demonstrates how the clustering of PK curves may generate insights that could be difficult to perceive solely with population level summary statistics of PK metrics.Comment: 38 pages, 14 figures, 3 table