The effect of a clinical practicum on elementary education preservice teachers' development of reading expertise

The purpose of the study was to measure gains in the development of elementary education teachers’ reading expertise, to determine if there was a differential gain in reading expertise, and last, to examine their perceptions of acquiring reading expertise. This research is needed in the field of teacher education, specifically in the field of reading. A quasi-experimental design with a comparison group using pretest-posttest mixed-method, repeated measures was utilized. Quantitative data analysis measured the development of reading expertise of elementary preservice teachers compared to early childhood preservice teachers; and, was used to examine the differential gains in reading expertise. A multivariate analysis of variance (MANOVA) was conducted on pre- and posttest responses on a Protocol of Questions. Further analysis was conducted on five variables (miscue analysis, fluency analysis, data analysis, inquiry orientation and intelligent action) using a univariate analysis of variance (ANOVA). A one-way ANOVA was carried out on gain scores of the low and middle groups of elementary education preservice teachers. Qualitative data analysis suggested by Merriam (1989) and Miles and Huberman (1994) was used to determine if the elementary education preservice teachers perceived they had acquired the expertise to teach reading. Elementary education preservice teachers who participated in a supervised clinical practicum made significant gains in their development of reading expertise as compared to early childhood preservice teachers who did not make significant gains. Elementary education preservice teachers who were in the low and middle third levels of expertise at pretest demonstrated significant gains in reading expertise. Last, elementary education preservice teachers perceived they had acquired the expertise to teach reading. The study concluded that reading expertise can be developed in elementary education preservice teachers through participation in a supervised clinical practicum. The findings support the idea that preservice teachers who will be teaching reading to elementary students would benefit from a supervised clinical practicum.

Development, validation and uncertainty analysis of quantitative structure and activity relationship models for Log P of disinfection by -products

Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.

Fiscal and organizational determinants of transportation outcomes: A quantitative and qualitative analysis of sustainability factors

Federal transportation legislation in effect since 1991 was examined to determine outcomes in two areas: (1) The effect of organizational and fiscal structures on the implementation of multimodal transportation infrastructure, and (2) The effect of multimodal transportation infrastructure on sustainability. Triangulation of methods was employed through qualitative analysis (including key informant interviews, focus groups and case studies), as well as quantitative analysis (including one-sample t-tests, regression analysis and factor analysis). ^ Four hypotheses were directly tested: (1) Regions with consolidated government structures will build more multimodal transportation miles: The results of the qualitative analysis do not lend support while the results of the quantitative findings support this hypothesis, possibly due to differences in the definitions of agencies/jurisdictions between the two methods. (2) Regions in which more locally dedicated or flexed funding is applied to the transportation system will build a greater number of multimodal transportation miles: Both quantitative and qualitative research clearly support this hypothesis. (3) Cooperation and coordination, or, conversely, competition will determine the number of multimodal transportation miles: Participants tended to agree that cooperation, coordination and leadership are imperative to achieving transportation goals and objectives, including targeted multimodal miles, but also stressed the importance of political and financial elements in determining what ultimately will be funded and implemented. (4) The modal outcomes of transportation systems will affect the overall health of a region in terms of sustainability/quality of life indicators: Both the qualitative and the quantitative analyses provide evidence that they do. ^ This study finds that federal legislation has had an effect on the modal outcomes of transportation infrastructure and that there are links between these modal outcomes and the sustainability of a region. It is recommended that agencies further consider consolidation and strengthen cooperation efforts and that fiscal regulations are modified to reflect the problems cited in qualitative analysis. Limitations of this legislation especially include the inability to measure sustainability; several measures are recommended. ^

Business process quantitative analysis and optimization for service industries

The total time a customer spends in the business process system, called the customer cycle-time, is a major contributor to overall customer satisfaction. Business process analysts and designers are frequently asked to design process solutions with optimal performance. Simulation models have been very popular to quantitatively evaluate the business processes; however, simulation is time-consuming and it also requires extensive modeling experiences to develop simulation models. Moreover, simulation models neither provide recommendations nor yield optimal solutions for business process design. A queueing network model is a good analytical approach toward business process analysis and design, and can provide a useful abstraction of a business process. However, the existing queueing network models were developed based on telephone systems or applied to manufacturing processes in which machine servers dominate the system. In a business process, the servers are usually people. The characteristics of human servers should be taken into account by the queueing model, i.e. specialization and coordination. ^ The research described in this dissertation develops an open queueing network model to do a quick analysis of business processes. Additionally, optimization models are developed to provide optimal business process designs. The queueing network model extends and improves upon existing multi-class open-queueing network models (MOQN) so that the customer flow in the human-server oriented processes can be modeled. The optimization models help business process designers to find the optimal design of a business process with consideration of specialization and coordination. ^ The main findings of the research are, first, parallelization can reduce the cycle-time for those customer classes that require more than one parallel activity; however, the coordination time due to the parallelization overwhelms the savings from parallelization under the high utilization servers since the waiting time significantly increases, thus the cycle-time increases. Third, the level of industrial technology employed by a company and coordination time to mange the tasks have strongest impact on the business process design; as the level of industrial technology employed by the company is high; more division is required to improve the cycle-time; as the coordination time required is high; consolidation is required to improve the cycle-time. ^

The discrimination and association of float glass and the quantitative analysis of liquids from aerosols and microdrops using laser induced breakdown spectroscopy

Glass is a common form of trace evidence found at many scenes of crimes in the form of small fragments. These glass fragments can transfer to surrounding objects and/or persons and may provide forensic investigators valuable information to link a suspect to the scene of a crime. Since the elemental composition of different glass sources can be very similar, a highly discriminating technique is required to distinguish between fragments that have originated from different sources. ^ The research presented here demonstrates that Laser Induced Breakdown Spectroscopy (LIBS) is a viable analytical technique for the association and discrimination of glass fragments. The first part of this research describes the optimization of the LIBS experiments including the use of different laser wavelengths to investigate laser-material interaction. The use of a 266 nm excitation laser provided the best analytical figures of merit with minimal damage to the sample. The resulting analytical figures of merit are presented. The second part of this research evaluated the sensitivity of LIBS to associate or discriminate float glass samples originating from the same manufacturing plants and produced at approximately the same time period. Two different sample sets were analyzed ranging in manufacturing dates from days to years apart. Eighteen (18) atomic emission lines corresponding to the elements Sr, K, Fe, Ca, Al, Ba, Na, Mg and Ti, were chosen because of their detection above the method detection limits and for presenting differences between the samples. Ten elemental ratios producing the most discrimination were selected for each set. When all the ratios are combined in a comparison, 99% of the possible pairs were discriminated using the optimized LIBS method generating typical analytical precisions of ∼5% RSD. ^ The final study consisted of the development of a new approach for the use of LIBS as a quantitative analysis of ultra-low volume solution analysis using aerosols and microdrops. Laser induced breakdown spectroscopy demonstrated to be an effective technique for the analysis of as low as 90 pL for microdrop LIBS with 1 pg absolute LOD and 20 µL for aerosol LIBS with an absolute LOD of ∼100 fg.^

Quantitative and Qualitative Aspects of Dissolved Organic Carbon Leached from Senescent Plants in an Oligotrophic Wetland

We conducted a series of experiments whereby dissolved organic matter (DOM) was leached from various wetland and estuarine plants, namely sawgrass (Cladium jamaicense), spikerush (Eleocharis cellulosa), red mangrove (Rhizophora mangle), cattail (Typha domingensis), periphyton (dry and wet mat), and a seagrass (turtle grass; Thalassia testudinum). All are abundant in the Florida Coastal Everglades (FCE) except for cattail, but this species has a potential to proliferate in this environment. Senescent plant samples were immersed into ultrapure water with and without addition of 0.1% NaN3 (w/ and w/o NaN3, respectively) for 36 days. We replaced the water every 3 days. The amount of dissolved organic carbon (DOC), sugars, and phenols in the leachates were analyzed. The contribution of plant leachates to the ultrafiltered high molecular weight fraction of DOM (>1 kDa; UDOM) in natural waters in the FCE was also investigated. UDOM in plant leachates was obtained by tangential flow ultrafiltration and its carbon and phenolic compound compositions were analyzed using solid state 13C cross-polarization magic angle spinning nuclear magnetic resonance (13C CPMAS NMR) spectroscopy and thermochemolysis in the presence of tetramethylammonium hydroxide (TMAH thermochemolysis), respectively. The maximum yield of DOC leached from plants over the 36-day incubations ranged from 13.0 to 55.2 g C kg−1 dry weight. This amount was lower in w/o NaN3 treatments (more DOC was consumed by microbes than produced) except for periphyton. During the first 2 weeks of the 5 week incubation period, 60–85% of the total amount of DOC was leached, and exponential decay models fit the leaching rates except for periphyton w/o NaN3. Leached DOC (w/ NaN3) contained different concentrations of sugars and phenols depending on the plant types (1.09–7.22 and 0.38–12.4 g C kg−1 dry weight, respectively), and those biomolecules comprised 8–34% and 4–28% of the total DOC, respectively. This result shows that polyphenols that readily leach from senescent plants can be an important source of chromophoric DOM (CDOM) in wetland environments. The O-alkyl C was found to be the major C form (55±9%) of UDOM in plant leachates as determined by 13C CPMAS NMR. The relative abundance of alkyl C and carbonyl C was consistently lower in plant-leached UDOM than that in natural water UDOM in the FCE, which suggests that these constituents increase in relative abundance during diagenetic processing. TMAH thermochemolysis analysis revealed that the phenolic composition was different among the UDOM leached from different plants, and was expected to serve as a source indicator of UDOM in natural water. Polyphenols are, however, very reactive and photosensitive in aquatic environments, and thus may loose their plant-specific molecular characteristics shortly. Our study suggests that variations in vegetative cover across a wetland landscape will affect the quantity and quality of DOM leached into the water, and such differences in DOM characteristics may affect other biogeochemical processes.

Two-bit pattern analysis for quantitative information flow

Protecting confidential information from improper disclosure is a fundamental security goal. While encryption and access control are important tools for ensuring confidentiality, they cannot prevent an authorized system from leaking confidential information to its publicly observable outputs, whether inadvertently or maliciously. Hence, secure information flow aims to provide end-to-end control of information flow. Unfortunately, the traditionally-adopted policy of noninterference, which forbids all improper leakage, is often too restrictive. Theories of quantitative information flow address this issue by quantifying the amount of confidential information leaked by a system, with the goal of showing that it is intuitively "small" enough to be tolerated. Given such a theory, it is crucial to develop automated techniques for calculating the leakage in a system. ^ This dissertation is concerned with program analysis for calculating the maximum leakage, or capacity, of confidential information in the context of deterministic systems and under three proposed entropy measures of information leakage: Shannon entropy leakage, min-entropy leakage, and g-leakage. In this context, it turns out that calculating the maximum leakage of a program reduces to counting the number of possible outputs that it can produce. ^ The new approach introduced in this dissertation is to determine two-bit patterns, the relationships among pairs of bits in the output; for instance we might determine that two bits must be unequal. By counting the number of solutions to the two-bit patterns, we obtain an upper bound on the number of possible outputs. Hence, the maximum leakage can be bounded. We first describe a straightforward computation of the two-bit patterns using an automated prover. We then show a more efficient implementation that uses an implication graph to represent the two- bit patterns. It efficiently constructs the graph through the use of an automated prover, random executions, STP counterexamples, and deductive closure. The effectiveness of our techniques, both in terms of efficiency and accuracy, is shown through a number of case studies found in recent literature. ^

Quantitative Analysis and Determination of Microcystin in water by Capillary Electrophoresis Mass Spectrometry

The presence of harmful algal blooms (HAB) is a growing concern in aquatic environments. Among HAB organisms, cyanobacteria are of special concern because they have been reported worldwide to cause environmental and human health problem through contamination of drinking water. Although several analytical approaches have been applied to monitoring cyanobacteria toxins, conventional methods are costly and time-consuming so that analyses take weeks for field sampling and subsequent lab analysis. Capillary electrophoresis (CE) becomes a particularly suitable analytical separation method that can couple very small samples and rapid separations to a wide range of selective and sensitive detection techniques. This paper demonstrates a method for rapid separation and identification of four microcystin variants commonly found in aquatic environments. CE coupled to UV and electrospray ionization time-of-flight mass spectrometry (ESI-TOF) procedures were developed. All four analytes were separated within 6 minutes. The ESI-TOF experiment provides accurate molecular information, which further identifies analytes.