Environment, Culture, and Medicinal Plant Knowledge in an Indigenous Amazonian Community

Diminishing cultural and biological diversity is a current global crisis. Tropical forests and indigenous peoples are adversely affected by social and environmental changes caused by global political and economic systems. The purpose of this thesis was to investigate environmental and livelihood challenges as well as medicinal plant knowledge in a Yagua village in the Peruvian Amazon. Indigenous peoples’ relationships with the environment is an important topic in environmental anthropology, and traditional botanical knowledge is an integral component of ethnobotany. Political ecology provides a useful theoretical perspective for understanding the economic and political dimensions of environmental and social conditions. This research utilized a variety of ethnographic, ethnobotanical, and community-involved methods. Findings include data and analyses about the community’s culture, subsistence and natural resource needs, organizations and institutions, and medicinal plant use. The conclusion discusses the case study in terms of the disciplinary framework and offers suggestions for research and application.

An Integrated Flow and Transport Model to Study the Impact of Mercury Remediation Strategies for East Fork Poplar Creek Watershed, Oak Ridge, Tennessee

An integrated flow and transport model using MIKE SHE/MIKE 11 software was developed to predict the flow and transport of mercury, Hg(II), under varying environmental conditions. The model analyzed the impact of remediation scenarios within the East Fork Poplar Creek watershed of the Oak Ridge Reservation with respect to downstream concentration of mercury. The numerical simulations included the entire hydrological cycle: flow in rivers, overland flow, groundwater flow in the saturated and unsaturated zones, and evapotranspiration and precipitation time series. Stochastic parameters and hydrologic conditions over a five year period of historical hydrological data were used to analyze the hydrological cycle and to determine the prevailing mercury transport mechanism within the watershed. Simulations of remediation scenarios revealed that reduction of the highly contaminated point sources, rather than general remediation of the contaminant plume, has a more direct impact on downstream mercury concentrations.

Estimation of Ravine Sediment Production and Sediment Dynamics in the Lower Le Sueur River Watershed, Minnesota

This study focuses on quantifying explicitly the sediment budget of deeply incised ravines in the lower Le Sueur River watershed, in southern Minnesota. High-rate-gully-erosion equations along with the Universal Soil Loss Equation (USLE) were implemented in a numerical modeling approach that is based on a time-integration of the sediment balance equations. The model estimates the rates of ravine width and depth change and the amount of sediment periodically flushing from the ravines. Components of the sediment budget of the ravines were simulated with the model and results suggest that the ravine walls are the major sediment source in the ravines. A sensitivity analysis revealed that the erodibility coefficients of the gully bed and wall, the local slope angle and the Manning’s coefficient are the key parameters controlling the rate of sediment production. Recommendations to guide further monitoring efforts in the watershed and increased detail modeling approaches are highlighted as a result of this modeling effort.

Glycemic Control: Risk Factors, Quality of Life, Workforce Participation, and Mortality Among US Adults with Type 2 Diabetes

Despite research showing the benefits of glycemic control, it remains suboptimal among adults with diabetes in the United States. Possible reasons include unaddressed risk factors as well as lack of awareness of its immediate and long term consequences. The objectives of this study were to, using cross-sectional data, 1) ascertain the association between suboptimal (Hemoglobin A1c (HbA1c) ≥7%), borderline (HbA1c 7-8.9%), and poor (HbA1c ≥9%) glycemic control and potentially new risk factors (e.g. work characteristics), and 2) assess whether aspects of poor health and well-being such as poor health related quality of life (HRQOL), unemployment, and missed-work are associated with glycemic control; and 3) using prospective data, assess the relationship between mortality risk and glycemic control in US adults with type 2 diabetes. Data from the 1988-1994 and 1999-2004 National Health and Nutrition Examination Surveys were used. HbA1c values were used to create dichotomous glycemic control indicators. Binary logistic regression models were used to assess relationships between risk factors, employment status and glycemic control. Multinomial logistic regression analyses were conducted to assess relationships between glycemic control and HRQOL variables. Zero-inflated Poisson regression models were used to assess relationships between missed work days and glycemic control. Cox-proportional hazard models were used to assess effects of glycemic control on mortality risk. Using STATA software, analyses were weighted to account for complex survey design and non-response. Multivariable models adjusted for socio-demographics, body mass index, among other variables. Results revealed that being a farm worker and working over 40 hours/week were risk factors for suboptimal glycemic control. Having greater days of poor mental was associated with suboptimal, borderline, and poor glycemic control. Having greater days of inactivity was associated with poor glycemic control while having greater days of poor physical health was associated with borderline glycemic control. There were no statistically significant relationships between glycemic control, self-reported general health, employment, and missed work. Finally, having an HbA1c value less than 6.5% was protective against mortality. The findings suggest that work-related factors are important in a person’s ability to reach optimal diabetes management levels. Poor glycemic control appears to have significant detrimental effects on HRQOL.

Through the Prisms of Gender and Power: Agency in International Courtship between Colombian Women and American Men

Since 1999 Colombia has experienced dramatic increases in emigration, particularly the emigration of women towards the U.S. as fiancées of U.S. citizens or residents. Parallel to this trend is the increased number of websites facilitating these Colombian-American matches. This dissertation investigates the agency of Colombian women and American men who pursue romantic courtship through the services of International Marriage Brokers (IMBs) from the “Gendered Geographies of Power” (GGP) framework of analysis. It examines how both groups’ social locations, their positioning in multiple axes of differentiation including gender, nationality and social class, affects how and why they exert their agency across and within different geographic scales. Most importantly, it investigates the role the imagination plays (imagination work) in both men and women’s agency, an aspect of the GGP framework that has been under-researched and theorized to date. The research also finds that this imagination work is promoted and cultivated in deeply gendered ways by IMBs seeking to profit off this transnational courtship. Employing data collected via interviews and content analysis of IMBs’ websites, the dissertation analyzes comparatively the expectations each group (women, men and IMBs) bring to their imagination work and experiences of the courtship marketplace. A central question posed and answered in the dissertation is “What do women and men courting each other in cyberspace seek and do they find it?” The dissertation finds that the men seek “traditional” women and the women seek “liberated” less “macho” men. Ironically, the men find Colombian women who are among the most “liberated” women in their homeland but who downplay this aspect of themselves in order to strategically find a more modern man and migrate abroad where they expect to find greater personal and professional opportunities.

The Construction and Optimization on an Ion Mobility Spectrometer for the Analysis of Explosives and Drugs

Today, over 15,000 Ion Mobility Spectrometry (IMS) analyzers are employed at worldwide security checkpoints to detect explosives and illicit drugs. Current portal IMS instruments and other electronic nose technologies detect explosives and drugs by analyzing samples containing the headspace air and loose particles residing on a surface. Canines can outperform these systems at sampling and detecting the low vapor pressure explosives and drugs, such as RDX, PETN, cocaine, and MDMA, because these biological detectors target the volatile signature compounds available in the headspace rather than the non-volatile parent compounds of explosives and drugs. In this dissertation research volatile signature compounds available in the headspace over explosive and drug samples were detected using SPME as a headspace sampling tool coupled to an IMS analyzer. A Genetic Algorithm (GA) technique was developed to optimize the operating conditions of a commercial IMS (GE Itemizer 2), leading to the successful detection of plastic explosives (Detasheet, Semtex H, and C-4) and illicit drugs (cocaine, MDMA, and marijuana). Short sampling times (between 10 sec to 5 min) were adequate to extract and preconcentrate sufficient analytes (> 20 ng) representing the volatile signatures in the headspace of a 15 mL glass vial or a quart-sized can containing ≤ 1 g of the bulk explosive or drug. Furthermore, a research grade IMS with flexibility for changing operating conditions and physical configurations was designed and fabricated to accommodate future research into different analytes or physical configurations. The design and construction of the FIU-IMS were facilitated by computer modeling and simulation of ion’s behavior within an IMS. The simulation method developed uses SIMION/SDS and was evaluated with experimental data collected using a commercial IMS (PCP Phemto Chem 110). The FIU-IMS instrument has comparable performance to the GE Itemizer 2 (average resolving power of 14, resolution of 3 between two drugs and two explosives, and LODs range from 0.7 to 9 ng). The results from this dissertation further advance the concept of targeting volatile components to presumptively detect the presence of concealed bulk explosives and drugs by SPME-IMS, and the new FIU-IMS provides a flexible platform for future IMS research projects.

Principal Component Analysis and Assessment of Language Network Activation Patterns in Pediatric Epilepsy

This dissertation establishes a novel data-driven method to identify language network activation patterns in pediatric epilepsy through the use of the Principal Component Analysis (PCA) on functional magnetic resonance imaging (fMRI). A total of 122 subjects’ data sets from five different hospitals were included in the study through a web-based repository site designed here at FIU. Research was conducted to evaluate different classification and clustering techniques in identifying hidden activation patterns and their associations with meaningful clinical variables. The results were assessed through agreement analysis with the conventional methods of lateralization index (LI) and visual rating. What is unique in this approach is the new mechanism designed for projecting language network patterns in the PCA-based decisional space. Synthetic activation maps were randomly generated from real data sets to uniquely establish nonlinear decision functions (NDF) which are then used to classify any new fMRI activation map into typical or atypical. The best nonlinear classifier was obtained on a 4D space with a complexity (nonlinearity) degree of 7. Based on the significant association of language dominance and intensities with the top eigenvectors of the PCA decisional space, a new algorithm was deployed to delineate primary cluster members without intensity normalization. In this case, three distinct activations patterns (groups) were identified (averaged kappa with rating 0.65, with LI 0.76) and were characterized by the regions of: 1) the left inferior frontal Gyrus (IFG) and left superior temporal gyrus (STG), considered typical for the language task; 2) the IFG, left mesial frontal lobe, right cerebellum regions, representing a variant left dominant pattern by higher activation; and 3) the right homologues of the first pattern in Broca's and Wernicke's language areas. Interestingly, group 2 was found to reflect a different language compensation mechanism than reorganization. Its high intensity activation suggests a possible remote effect on the right hemisphere focus on traditionally left-lateralized functions. In retrospect, this data-driven method provides new insights into mechanisms for brain compensation/reorganization and neural plasticity in pediatric epilepsy.

Headspace Analysis of Smokeless Powders: Development of Mass Calibration Methods using Microdrop Printing for Chromatographic and Ion Mobility Spectrometric Detection

Smokeless powder additives are usually detected by their extraction from post-blast residues or unburned powder particles followed by analysis using chromatographic techniques. This work presents the first comprehensive study of the detection of the volatile and semi-volatile additives of smokeless powders using solid phase microextraction (SPME) as a sampling and pre-concentration technique. Seventy smokeless powders were studied using laboratory based chromatography techniques and a field deployable ion mobility spectrometer (IMS). The detection of diphenylamine, ethyl and methyl centralite, 2,4-dinitrotoluene, diethyl and dibutyl phthalate by IMS to associate the presence of these compounds to smokeless powders is also reported for the first time. A previously reported SPME-IMS analytical approach facilitates rapid sub-nanogram detection of the vapor phase components of smokeless powders. A mass calibration procedure for the analytical techniques used in this study was developed. Precise and accurate mass delivery of analytes in picoliter volumes was achieved using a drop-on-demand inkjet printing method. Absolute mass detection limits determined using this method for the various analytes of interest ranged between 0.03 - 0.8 ng for the GC-MS and between 0.03 - 2 ng for the IMS. Mass response graphs generated for different detection techniques help in the determination of mass extracted from the headspace of each smokeless powder. The analyte mass present in the vapor phase was sufficient for a SPME fiber to extract most analytes at amounts above the detection limits of both chromatographic techniques and the ion mobility spectrometer. Analysis of the large number of smokeless powders revealed that diphenylamine was present in the headspace of 96% of the powders. Ethyl centralite was detected in 47% of the powders and 8% of the powders had methyl centralite available for detection from the headspace sampling of the powders by SPME. Nitroglycerin was the dominant peak present in the headspace of the double-based powders. 2,4-dinitrotoluene which is another important headspace component was detected in 44% of the powders. The powders therefore have more than one headspace component and the detection of a combination of these compounds is achievable by SPME-IMS leading to an association to the presence of smokeless powders.

Class Placement and Academic and Behavioral Variables as Predictors of Graduation for Students with Disabilities

Dropout rates impacting students with high-incidence disabilities in American schools remain staggering (Bost, 2006; Hehir, 2005). Of this group, students with Emotional Behavioral Disorders (EBD) are at greatest risk. Despite the mandated national propagation of inclusion, students with EBD remain the least included and the least successful when included (Bost). Accordingly, this study investigated the potential significance of inclusive settings and other school-related variables within the context of promoting the graduation potential of students with Specific Learning Disabilities (SLD) or EBD. This mixed-methods study investigated specified school-related variables as likely dropout predictors, as well as the existence of first-order interactions among some of the variables. In addition, it portrayed the perspectives of students with SLD or EBD on the school-related variables that promote graduation. Accordingly, the sample was limited to students with SLD or EBD who had graduated or were close to graduation. For the quantitative component the numerical data were analyzed using linear and logistic regressions. For the qualitative component guided student interviews were conducted. Both strands were subsequently analyzed using Ridenour and Newman’s (2008) model where the quantitative hypotheses are tested and are later built-upon by the related qualitative meta-themes. Results indicated that a successful academic history, or obtaining passing grades was the only significant predictor of graduation potential when statistically controlling all the other variables. While at a marginal significance, results also yielded that students with SLD or EBD in inclusive settings experienced better academic results and behavioral outcomes than those in self-contained settings. Specifically, students with SLD or EBD in inclusive settings were found to be more likely to obtain passing grades and less likely to be suspended from school. Generally, the meta-themes yielded during the student interviews corroborated these findings as well as provided extensive insights on how students with disabilities view school within the context of promoting graduation. Based on the results yielded, provided the necessary academic accommodations and adaptations are in place, along with an effective behavioral program, inclusive settings can be utilized as drop-out prevention tools in special education.

The Effects of American Sign Language on General Self- Efficacy and Anxiety Among Mothers in a Residential Rehabilitation Facility for Drug Addiction and Substance Abuse

Globally, approximately 208 million people aged 15 and older used illicit drugs at least once in the last 12 months; 2 billion consumed alcohol and tobacco consumption affected 25% (World Drug Report, 2008). In the United States, 20.1 million (8.0%) people aged 12 and older were illicit drug users, 129 million (51.6%) abused alcohol and 70.9 million (28.4%) used tobacco (SAMHSA/OAS, 2008).Usually considered a problem specific to men (Lynch, 2002), 5.2% of pregnant women aged 15 to 44 are also illicit drug and substance abusers (SAMHSA/OAS, 2007). During pregnancy, illicit drugs and substance abuse (ID/SA) can significantly affect a woman and her infant contributing to developmental and communication delays for the infant and influencing parenting abilities (Budden, 1996; March of Dimes, 2006b; Rossetti, 2000). Feelings of guilt and shame and stressful experiences influence approaches to parenting (Ashley, Marsden, & Brady, 2003; Brazelton, & Greenspan, 2000; Ehrmin, 2000; Johnson, & Rosen, 1990; Kelley, 1998; Rossetti, 2000; Velez et al., 2004; Zickler, 1999). Parenthood is an expanded role that can be a trying time for those lacking a sense of self-efficacy and creates a high vulnerability to stress (Bandura, 1994). Residential treatment programs for ID/SA mothers and their children provide an excellent opportunity for effective interventions (Finkelstein, 1994; Social Care Institute for Excellence, 2005). This experimental study evaluated whether teaching American Sign Language (ASL) to mothers living with their infants/children at an ID/SA residential treatment program increased the mothers’ self-efficacy and decreased their anxiety. Quantitative data were collected using the General Self-Efficacy Scale and the State-Trait Anxiety Inventory showing there was both a significant increase in self efficacy and decrease in anxiety for the mothers. This research adds to the knowledge base concerning ID/SA mothers’ caring for their infants/children. By providing a simple low cost program, easily incorporated into existing rehabilitation curricula, the study helps educators and healthcare providers better understand the needs of the ID/SA mothers. This study supports Bandura’s theory that parents who are secure in their efficacy can navigate through the various phases of their child’s development and are less vulnerable to stress (Bandura, 1994).

Resource, Strategies, Location Determinants, And Host Country Location Choice By Emerging Market Firms

The extant literature had studied the determinants of the firms’ location decisions with help of host country characteristics and distances between home and host countries. Firm resources and its internationalization strategies had found limited attention in this literature. To address this gap, the research question in this dissertation was whether and how firms’ resources and internationalization strategies impacted the international location decisions of emerging market firms. To explore the research question, data were hand-collected from Indian software firms on their location decisions taken between April 2000 and March 2009. To analyze the multi-level longitudinal dataset, hierarchical linear modeling was used. The results showed that the internationalization strategies, namely market-seeking or labor-seeking had direct impact on firms’ location decision. This direct relationship was moderated by firm resource which, in case of Indian software firms, was the appraisal at CMMI level-5. Indian software firms located in developed countries with a market-seeking strategy and in emerging markets with a labor-seeking strategy. However, software firms with resource such as CMMI level-5 appraisal, when in a labor-seeking mode, were more likely to locate in a developed country over emerging market than firms without the appraisal. Software firms with CMMI level-5 appraisal, when in market-seeking mode, were more likely to locate in a developed country over an emerging market than firms without the appraisal. It was concluded that the internationalization strategies and resources of companies predicted their location choices, over and above the variables studied in the theoretical field of location determinants.

Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-Order Operations

The increasing emphasis on mass customization, shortened product lifecycles, synchronized supply chains, when coupled with advances in information system, is driving most firms towards make-to-order (MTO) operations. Increasing global competition, lower profit margins, and higher customer expectations force the MTO firms to plan its capacity by managing the effective demand. The goal of this research was to maximize the operational profits of a make-to-order operation by selectively accepting incoming customer orders and simultaneously allocating capacity for them at the sales stage. For integrating the two decisions, a Mixed-Integer Linear Program (MILP) was formulated which can aid an operations manager in an MTO environment to select a set of potential customer orders such that all the selected orders are fulfilled by their deadline. The proposed model combines order acceptance/rejection decision with detailed scheduling. Experiments with the formulation indicate that for larger problem sizes, the computational time required to determine an optimal solution is prohibitive. This formulation inherits a block diagonal structure, and can be decomposed into one or more sub-problems (i.e. one sub-problem for each customer order) and a master problem by applying Dantzig-Wolfe’s decomposition principles. To efficiently solve the original MILP, an exact Branch-and-Price algorithm was successfully developed. Various approximation algorithms were developed to further improve the runtime. Experiments conducted unequivocally show the efficiency of these algorithms compared to a commercial optimization solver. The existing literature addresses the static order acceptance problem for a single machine environment having regular capacity with an objective to maximize profits and a penalty for tardiness. This dissertation has solved the order acceptance and capacity planning problem for a job shop environment with multiple resources. Both regular and overtime resources is considered. The Branch-and-Price algorithms developed in this dissertation are faster and can be incorporated in a decision support system which can be used on a daily basis to help make intelligent decisions in a MTO operation.

The Perceptions, Attitudes and Practices of Registered Dietitians Regarding Functional Foods

The term “functional food” (FF) has a variety of definitions resulting in term ambiguity. It is unclear Registered Dietitians’ (RDs) understanding and practices about FF. A descriptive, cross-sectional study investigated RDs’ perceptions, attitudes and practices regarding FF. A national random sample (n=1800) of RDs was mailed a FF questionnaire, 385 (22%) responded. Given five definitions from food-nutrition authorities, the majority of RDs did not agree on a definition, although three-fourths (n=292, 75.8%) perceived fortified foods as FF. Registered Dietitians agreed FF could improve health (n=266, 69.1%), prevent disease (n=282, 73.2%) and treat clientele (n=246, 63.9%), however were neutral (41.6%) or disagreed (37.7%) FF were herbs, or equivalent to medicine (32.7%, 49.2% respectively). Most RDs (n=290, 75.9%) ate FF; fewer (n=231, 61.4%) professionally recommended them. Nearly all (n=353) indicated interest in learning about FF. Registered Dietitians revealed inconsistencies between their perceptions, attitudes and practices regarding FF. Professional education is needed to resolve discrepancies regarding FF.

Tailoring Heme-Thiolate Proteins into Efficient Biocatalysts with High Specificity and Selectivity

Cytochrome P450 monooxygenases, one of the most important classes of heme-thiolate proteins, have attracted considerable interest in the biochemical community because of its catalytic versatility, substrate diversity and great number in the superfamily. Although P450s are capable of catalyzing numerous difficult oxidation reactions, the relatively low stability, low turnover rates and the need of electron-donating cofactors have limited their practical biotechnological and pharmaceutical applications as isolated enzymes. The goal of this study is to tailor such heme-thiolate proteins into efficient biocatalysts with high specificity and selectivity by protein engineering and to better understand the structure-function relationship in cytochromes P450. In the effort to engineer P450cam, the prototype member of the P450 superfamily, into an efficient peroxygenase that utilizes hydrogen peroxide via the “peroxide-shunt” pathway, site-directed mutagenesis has been used to elucidate the critical roles of hydrophobic residues in the active site. Various biophysical, biochemical and spectroscopic techniques have been utilized to investigate the wild-type and mutant proteins. Three important P450cam variants were obtained showing distinct structural and functional features. In P450camV247H mutant, which exhibited almost identical spectral properties with the wild-type, it is demonstrated that a single amino acid switch turned the monooxygenase into an efficient preoxidase by increasing the peroxidase activity nearly one thousand folds. In order to tune the distal pocket of P450cam with polar residues, Leu 246 was replaced with a basic residue, lysine, resulting in a mutant with spectral features identical to P420, the inactive species of P450. But this inactive-species-like mutant showed catalytic activities without the facilitation of any cofactors. By substituting Gly 248 with a histidine, a novel Cys-Fe-His ligation set was obtained in P450cam which represented the very rare case of His ligation in heme-thiolate proteins. In addition to serving as a convenient model for hemoprotein structural studies, the G248H mutant also provided evidence about the nature of the axial ligand in cytochrome P420 and other engineered hemoproteins with thiolate ligations. Furthermore, attempts have been made to replace the proximal ligand in sperm whale myoglobin to construct a heme-thiolate protein model by mimicking the protein environment of cytochrome P450cam and chloroperoxidase.

Analytical Approximations to Predict Performance Measures of Manufacturing Systems with Job Failures and Parallel Processing

Parallel processing is prevalent in many manufacturing and service systems. Many manufactured products are built and assembled from several components fabricated in parallel lines. An example of this manufacturing system configuration is observed at a manufacturing facility equipped to assemble and test web servers. Characteristics of a typical web server assembly line are: multiple products, job circulation, and paralleling processing. The primary objective of this research was to develop analytical approximations to predict performance measures of manufacturing systems with job failures and parallel processing. The analytical formulations extend previous queueing models used in assembly manufacturing systems in that they can handle serial and different configurations of paralleling processing with multiple product classes, and job circulation due to random part failures. In addition, appropriate correction terms via regression analysis were added to the approximations in order to minimize the gap in the error between the analytical approximation and the simulation models. Markovian and general type manufacturing systems, with multiple product classes, job circulation due to failures, and fork and join systems to model parallel processing were studied. In the Markovian and general case, the approximations without correction terms performed quite well for one and two product problem instances. However, it was observed that the flow time error increased as the number of products and net traffic intensity increased. Therefore, correction terms for single and fork-join stations were developed via regression analysis to deal with more than two products. The numerical comparisons showed that the approximations perform remarkably well when the corrections factors were used in the approximations. In general, the average flow time error was reduced from 38.19% to 5.59% in the Markovian case, and from 26.39% to 7.23% in the general case. All the equations stated in the analytical formulations were implemented as a set of Matlab scripts. By using this set, operations managers of web server assembly lines, manufacturing or other service systems with similar characteristics can estimate different system performance measures, and make judicious decisions - especially setting delivery due dates, capacity planning, and bottleneck mitigation, among others.