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. ^

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.

Stabilization of troponin I for applications in clinical chemistry and forensic medicine. Cardiac troponin I: A time of death marker

Cardiac troponin I (cTnI) is one of the most useful serum marker test for the determination of myocardial infarction (MI). The first commercial assay of cTnI was released for medical use in the United States and Europe in 1995. It is useful in determining if the source of chest pains, whose etiology may be unknown, is cardiac related. Cardiac TnI is released into the bloodstream following myocardial necrosis (cardiac cell death) as a result of an infarct (heart attack). In this research project the utility of cardiac troponin I as a potential marker for the determination of time of death is investigated. The approach of this research is not to investigate cTnI degradation in serum/plasma, but to investigate the proteolytic breakdown of this protein in heart tissue postmortem. If our hypothesis is correct, cTnI might show a distinctive temporal degradation profile after death. This temporal profile may have potential as a time of death marker in forensic medicine. The field of time of death markers has lagged behind the great advances in technology since the late 1850's. Today medical examiners are using rudimentary time of death markers that offer limited reliability in the medico-legal arena. Cardiac TnI must be stabilized in order to avoid further degradation by proteases in the extraction process. Chemically derivatized magnetic microparticles were covalently linked to anti-cTnI monoclonal antibodies. A charge capture approach was also used to eliminate the antibody from the magnetic microparticles given the negative charge on the microparticles. The magnetic microparticles were used to extract cTnI from heart tissue homogenate for further bio-analysis. Cardiac TnI was eluted from the beads with a buffer and analyzed. This technique exploits banding pattern on sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) followed by a western blot transfer to polyvinylidene fluoride (PVDF) paper for probing with anti-cTnI monoclonal antibodies. Bovine hearts were used as a model to establish the relationship of time of death and concentration/band-pattern given its homology to human cardiac TnI. The final concept feasibility was tested with human heart samples from cadavers with known time of death. ^

Spatial-temporal mining of archived automatic vehicle location (AVL) data for transit service planning applications

An Automatic Vehicle Location (AVL) system is a computer-based vehicle tracking system that is capable of determining a vehicle's location in real time. As a major technology of the Advanced Public Transportation System (APTS), AVL systems have been widely deployed by transit agencies for purposes such as real-time operation monitoring, computer-aided dispatching, and arrival time prediction. AVL systems make a large amount of transit performance data available that are valuable for transit performance management and planning purposes. However, the difficulties of extracting useful information from the huge spatial-temporal database have hindered off-line applications of the AVL data. ^ In this study, a data mining process, including data integration, cluster analysis, and multiple regression, is proposed. The AVL-generated data are first integrated into a Geographic Information System (GIS) platform. The model-based cluster method is employed to investigate the spatial and temporal patterns of transit travel speeds, which may be easily translated into travel time. The transit speed variations along the route segments are identified. Transit service periods such as morning peak, mid-day, afternoon peak, and evening periods are determined based on analyses of transit travel speed variations for different times of day. The seasonal patterns of transit performance are investigated by using the analysis of variance (ANOVA). Travel speed models based on the clustered time-of-day intervals are developed using important factors identified as having significant effects on speed for different time-of-day periods. ^ It has been found that transit performance varied from different seasons and different time-of-day periods. The geographic location of a transit route segment also plays a role in the variation of the transit performance. The results of this research indicate that advanced data mining techniques have good potential in providing automated techniques of assisting transit agencies in service planning, scheduling, and operations control. ^

Managing small-medium cities in a time of globalization: Experiences and evidence from Florida's public managers

This study examines how public management practitioners in small and medium-sized Florida cities perceive globalization and its impact on public management practice. Using qualitative analysis, descriptive statistics and factor analysis methods, data obtained from a survey and semi-structured interviews were studied to comprehend how public managers view the management and control of their municipalities in a time of globalization. The study shows that the public managers’ perceptions of globalization and its impact on public management in Florida’s small-medium cities are nuanced. Whereas some public managers feel that globalization has significant impacts on municipalities’ viability, others opine that globalization has no local impact. The study further finds that globalization processes are perceived as altering the public management functions of decision-making, economic development and service delivery in some small-medium cities in Florida as a result of transnational shifts, rapidly changing technologies, and municipalities’ heightened involvement in the global economy. The study concludes that the globalization discourse does not resonate among some public managers in Florida’s small-medium cities in ways implied in extant literature.

A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

Perceptions of French and Creole Among First-Generation Adult Haitian English Language Learners

Context: Due to a unique combination of factors, outdoor athletes in the Southeastern United States are at high risk of lightning deaths and injuries. Lightning detection methods are available to minimize lightning strike victims. Objective: Becoming aware of the risk factors that predispose athletes to lightning strikes and determining the most reliable detection method against hazardous weather will enable Certified Athletic Trainers to develop protocols that protect athletes from injury. Data Sources: A comprehensive literature review of Medline and Pubmed using key words: lightning, lightning risk factors, lightning safety, lightning detection, and athletic trainers and lightning was completed. Data Synthesis: Factors predisposing athletes to lighting death or injury include: time of year, time of day, the athlete’s age, geographical location, physical location, sex, perspiration level, and lack of education and preparedness by athletes and staff. Although handheld lightning detectors have become widely accessible to detect lightning strikes, their performance has not been independently or objectively confirmed. There is evidence that these detectors inaccurately detect strike locations by recording false strikes and not recording actual strikes. Conclusions: Lightning education and preparation are two factors that can be controlled. Measures need to be taken by Certified Athletic Trainers to ensure the safety of athletes during outdoor athletics. It is critical for athletic trainers and supervising staff members to become fully aware of the risks of lightning strikes in order to most effectively protect everyone under their supervision. Even though lightning detectors have been manufactured in an attempt to minimize death and injuries due to lightning strikes, none of the detectors have been proven to be 100% effective. Educating coaches, athletes, and parents on the risks of lightning and the detection methods available, while implementing an emergency action plan for lightning safety, is crucial to ensure the well being of the student-athlete population.