Combination of 16S rRNA variable regions provides a detailed analysis of bacterial community dynamics in the lungs of cystic fibrosis patients

Chronic bronchopulmonary bacterial infections remain the most common cause of morbidity and mortality among patients with cystic fibrosis (CF). Recent community sequencing work has now shown that the bacterial community in the CF lung is polymicrobial. Identifying bacteria in the CF lung through sequencing can be costly and is not practical for many laboratories. Molecular techniques such as terminal restriction fragment length polymorphism or amplicon length heterogeneity-polymerase chain reaction (LH-PCR) can provide many laboratories with the ability to study CF bacterial communities without costly sequencing. The aim of this study was to determine if the use of LH-PCR with multiple hypervariable regions of the 16S rRNA gene could be used to identify organisms found in sputum DNA. This work also determined if LH-PCR could be used to observe the dynamics of lung infections over a period of time. Nineteen samples were analysed with the V1 and the V1_V2 region of the 16S rRNA gene. Based on the amplicon size present in the V1_V2 region, Pseudomonas aeruginosa was confirmed to be in all 19 samples obtained from the patients. The V1 region provided a higher power of discrimination between bacterial profiles of patients. Both regions were able to identify trends in the bacterial population over a period of time. LH profiles showed that the CF lung community is dynamic and that changes in the community may in part be driven by the patient's antibiotic treatment. LH-PCR is a tool that is well suited for studying bacterial communities and their dynamics.

Elementary music and classroom teachers' time -use: A comparison by grade level, time of day, and day of the week

This study investigated time-use of elementary music teachers and elementary classroom teachers to determine: (1) whether there was a relationship between grade level, time of day, and day of the week and teachers' time-use in teaching, monitoring, and non-curricular, and (2) whether ethnicity, training, and years of experience affect teacher time-use. Sixty-nine music teachers and 55 classroom teachers participated. ^ A MANOVA was used to examine the hypothesized relationship. ANOVA results were significant for time spent teaching, monitoring, and non-curricular. An independent t test revealed a significance difference (t (302) = 5.20, p < .001) between the two groups of teachers. A significant difference was found for teaching, t (302) = 5.20, p < .001: music teachers spent more time actively teaching than did classroom teachers. There was a significant difference for monitoring (t (302) = 13.62, p < .001): classroom teachers allocated more time to monitoring than did music teachers. A significant difference was also found for non-curricular (t (302) = 7.03, p < .001): music teachers spent more time in this category of activities than did classroom teachers. ^ Analyses of the activities subsumed under the major categories indicated significant differences between elementary music teachers and elementary classroom teachers, overall, in subject matter (p < .001), discussion (p < .05), school-wide activities (p < .001), seatwork (p < .001), giving directions (p < .001), changing activities (p < .001), lunch (p < .05), planning (p < .001) and interruption (p < .001). Analyses of the relationship and ethnicity, training, degree, experience indicated significant difference for main effect, ethnicity (F(2, 116) = 4.22, p < .017). Time-use for black non-Hispanic teachers was higher than time-use for those who were Hispanic and white non-Hispanic. ^ Analyses of time-use by grade showed no increase for either group as grade level increased. A statistically significant Wilks Lambda ( F (1,294) = .917 p < .013) was found for the independent variable day of the week. ANOVA indicated that elementary classroom teachers monitored more on Thursdays and Fridays: music teachers allocated more time to non-curricular activities on Fridays. ^

Incorporating variable peak -to -daily ratios in the equilibrium traffic assignment procedure of the Florida Standard Urban Transportation Modeling Structure (FSUTMS)

The standard highway assignment model in the Florida Standard Urban Transportation Modeling Structure (FSUTMS) is based on the equilibrium traffic assignment method. This method involves running several iterations of all-or-nothing capacity-restraint assignment with an adjustment of travel time to reflect delays encountered in the associated iteration. The iterative link time adjustment process is accomplished through the Bureau of Public Roads (BPR) volume-delay equation. Since FSUTMS' traffic assignment procedure outputs daily volumes, and the input capacities are given in hourly volumes, it is necessary to convert the hourly capacities to their daily equivalents when computing the volume-to-capacity ratios used in the BPR function. The conversion is accomplished by dividing the hourly capacity by a factor called the peak-to-daily ratio, or referred to as CONFAC in FSUTMS. The ratio is computed as the highest hourly volume of a day divided by the corresponding total daily volume. ^ While several studies have indicated that CONFAC is a decreasing function of the level of congestion, a constant value is used for each facility type in the current version of FSUTMS. This ignores the different congestion level associated with each roadway and is believed to be one of the culprits of traffic assignment errors. Traffic counts data from across the state of Florida were used to calibrate CONFACs as a function of a congestion measure using the weighted least squares method. The calibrated functions were then implemented in FSUTMS through a procedure that takes advantage of the iterative nature of FSUTMS' equilibrium assignment method. ^ The assignment results based on constant and variable CONFACs were then compared against the ground counts for three selected networks. It was found that the accuracy from the two assignments was not significantly different, that the hypothesized improvement in assignment results from the variable CONFAC model was not empirically evident. It was recognized that many other factors beyond the scope and control of this study could contribute to this finding. It was recommended that further studies focus on the use of the variable CONFAC model with recalibrated parameters for the BPR function and/or with other forms of volume-delay functions. ^

Space-for-Time Substitution Works in Everglades Ecological Forecasting Models

Space-for-time substitution is often used in predictive models because long-term time-series data are not available. Critics of this method suggest factors other than the target driver may affect ecosystem response and could vary spatially, producing misleading results. Monitoring data from the Florida Everglades were used to test whether spatial data can be substituted for temporal data in forecasting models. Spatial models that predicted bluefin killifish (Lucania goodei) population response to a drying event performed comparably and sometimes better than temporal models. Models worked best when results were not extrapolated beyond the range of variation encompassed by the original dataset. These results were compared to other studies to determine whether ecosystem features influence whether space-for-time substitution is feasible. Taken in the context of other studies, these results suggest space-for-time substitution may work best in ecosystems with low beta-diversity, high connectivity between sites, and small lag in organismal response to the driver variable.

Space-for-Time Substitution Works in Everglades Ecological Forecasting Models

Space-for-time substitution is often used in predictive models because long-term time-series data are not available. Critics of this method suggest factors other than the target driver may affect ecosystem response and could vary spatially, producing misleading results. Monitoring data from the Florida Everglades were used to test whether spatial data can be substituted for temporal data in forecasting models. Spatial models that predicted bluefin killifish (Lucania goodei) population response to a drying event performed comparably and sometimes better than temporal models. Models worked best when results were not extrapolated beyond the range of variation encompassed by the original dataset. These results were compared to other studies to determine whether ecosystem features influence whether space-for-time substitution is feasible. Taken in the context of other studies, these results suggest space-fortime substitution may work best in ecosystems with low beta-diversity, high connectivity between sites, and small lag in organismal response to the driver variable.

Elementary music and classroom teachers' time-use: a comparison by grade level, time of day, and day of the week

This study investigated time-use of elementary music teachers and elementary classroom teachers to determine: (1) whether there was a relationship between grade level, time of day, and day of the week and teachers' time-use in teaching, monitoring, and non-curricular, and (2) whether ethnicity, training, and years of experience affect teacher time-use. Sixty-nine music teachers and 55 classroom teachers participated. A MANOVA was used to examine the hypothesized relationship. ANOVA results were significant for time spent teaching, monitoring, and non-curricular. An independent t test revealed a significance difference (t (302) = 5.20, p Analyses of the activities subsumed under the major categories indicated significant differences between elementary music teachers and elementary classroom teachers, overall, in subject matter ( p teachers was higher than time-use for those who were Hispanic and white non-Hispanic. Analyses of time-use by grade showed no increase for either group as grade level increased. A statistically significant Wilks Lambda ( F (1,294) = .917 p < .013 ) was found for the independent variable day of the week. ANOVA indicated that elementary classroom teachers monitored more on Thursdays and Fridays: music teachers allocated more time to non-curricular activities on Fridays.

The Validity of Broad and Narrow Personality Traits For Predicting Job Performance: The Differential Effects of Time

Research into the dynamicity of job performance criteria has found evidence suggesting the presence of rank-order changes to job performance scores across time as well as intraindividual trajectories in job performance scores across time. These findings have influenced a large body of research into (a) the dynamicity of validities of individual differences predictors of job performance and (b) the relationship between individual differences predictors of job performance and intraindividual trajectories of job performance. In the present dissertation, I addressed these issues within the context of the Five Factor Model of personality. The Five Factor Model is arranged hierarchically, with five broad higher-order factors subsuming a number of more narrowly tailored personality facets. Research has debated the relative merits of broad versus narrow traits for predicting job performance, but the entire body of research has addressed the issue from a static perspective -- by examining the relative magnitude of validities of global factors versus their facets. While research along these lines has been enlightening, theoretical perspectives suggest that the validities of global factors versus their facets may differ in their stability across time. Thus, research is needed to not only compare the relative magnitude of validities of global factors versus their facets at a single point in time, but also to compare the relative stability of validities of global factors versus their facets across time. Also necessary to advance cumulative knowledge concerning intraindividual performance trajectories is research into broad vs. narrow traits for predicting such trajectories. In the present dissertation, I addressed these issues using a four-year longitudinal design. The results indicated that the validities of global conscientiousness were stable across time, while the validities of conscientiousness facets were more likely to fluctuate. However, the validities of emotional stability and extraversion facets were no more likely to fluctuate across time than those of the factors. Finally, while some personality factors and facets predicted performance intercepts (i.e., performance at the first measurement occasion), my results failed to indicate a significant effect of any personality variable on performance growth. Implications for research and practice are discussed.