Creating User-Friendly Tools for Data Analysis and Visualization in K-12 Classrooms: A Fortran Dinosaur Meets Generation Y

During the summer of 2007, as part of the second year of a NASA-funded project in partnership with Christopher Newport University called SPHERE (Students as Professionals Helping Educators Research the Earth), a group of undergraduate students spent 8 weeks in a research internship at or near NASA Langley Research Center. Three students from this group formed the Clouds group along with a NASA mentor (Chambers), and the brief addition of a local high school student fulfilling a mentorship requirement. The Clouds group was given the task of exploring and analyzing ground-based cloud observations obtained by K-12 students as part of the Students' Cloud Observations On-Line (S'COOL) Project, and the corresponding satellite data. This project began in 1997. The primary analysis tools developed for it were in FORTRAN, a computer language none of the students were familiar with. While they persevered through computer challenges and picky syntax, it eventually became obvious that this was not the most fruitful approach for a project aimed at motivating K-12 students to do their own data analysis. Thus, about halfway through the summer the group shifted its focus to more modern data analysis and visualization tools, namely spreadsheets and Google(tm) Earth. The result of their efforts, so far, is two different Excel spreadsheets and a Google(tm) Earth file. The spreadsheets are set up to allow participating classrooms to paste in a particular dataset of interest, using the standard S'COOL format, and easily perform a variety of analyses and comparisons of the ground cloud observation reports and their correspondence with the satellite data. This includes summarizing cloud occurrence and cloud cover statistics, and comparing cloud cover measurements from the two points of view. A visual classification tool is also provided to compare the cloud levels reported from the two viewpoints. This provides a statistical counterpart to the existing S'COOL data visualization tool, which is used for individual ground-to-satellite correspondences. The Google(tm) Earth file contains a set of placemarks and ground overlays to show participating students the area around their school that the satellite is measuring. This approach will be automated and made interactive by the S'COOL database expert and will also be used to help refine the latitude/longitude location of the participating schools. Once complete, these new data analysis tools will be posted on the S'COOL website for use by the project participants in schools around the US and the world

Poboljšan postupak sinteze nekih novih 1,3-diaril-2-propen-1-ona koristeći PEG-400 kao reciklirajuće otapalo i njihovo antimikrobno vrednovanje

A simple and convenient route is described for the synthesis of novel hetero 1,3-diaryl-2-propen-1-ones (chalcones) by using recyclable poly PEG-400 as an alternative reaction solvent. The reaction is clean with excellent yield, shorter reaction time and reduces the use of volatile organic compounds (VOCs). All the synthesized compounds were evaluated for their antimicrobial activities against several pathogenic representatives.Opisana je jednostavna i pogodna metoda sinteze novih hetero 1,3-diaril-2-propen-1-ona (kalkona) koristeći poli(etilenglikol) (PEG-400) kao alternativno otapalo. Reakcija je jednoznačna, a uporaba hlapljivih organskih otapala je smanjena. Iskorištenja na produktima su visoka, a reakcijska vremena kraća. Svi sintetizirani spojevi testirani su na antimikrobno djelovanje na nekoliko patogenih mikroorganizama

Urban Airborne Lead: X-Ray Absorption Spectroscopy Establishes Soil as Dominant Source

BACKGROUND: Despite the dramatic decrease in airborne lead over the past three decades, there are calls for regulatory limits on this potent pediatric neurotoxin lower even than the new (2008) US Environmental Protection Agency standard. To achieve further decreases in airborne lead, what sources would need to be decreased and what costs would ensue? Our aim was to identify and, if possible, quantify the major species (compounds) of lead in recent ambient airborne particulate matter collected in El Paso, TX, USA. METHODOLOGY/PRINCIPAL FINDINGS: We used synchrotron-based XAFS (x-ray absorption fine structure) to identify and quantify the major Pb species. XAFS provides molecular-level structural information about a specific element in a bulk sample. Pb-humate is the dominant form of lead in contemporary El Paso air. Pb-humate is a stable, sorbed complex produced exclusively in the humus fraction of Pb-contaminated soils; it also is the major lead species in El Paso soils. Thus such soil must be the dominant source, and its resuspension into the air, the transfer process, providing lead particles to the local air. CONCLUSIONS/SIGNIFICANCE: Current industrial and commercial activity apparently is not a major source of airborne lead in El Paso, and presumably other locales that have eliminated such traditional sources as leaded gasoline. Instead, local contaminated soil, legacy of earlier anthropogenic Pb releases, serves as a long-term reservoir that gradually leaks particulate lead to the atmosphere. Given the difficulty and expense of large-scale soil remediation or removal, fugitive soil likely constrains a lower limit for airborne lead levels in many urban settings

Greenhouse gas emissions from a Western Australian finfish supply chain

Greenhouse gas (GHG) emissions in the form of carbon dioxide equivalent (CO2 - eq) from two Western Australian finfish supply chains, from harvest to retail outlet, were measured using streamlined life cycle assessment methodology. The identification of interventions to potentially reduce the GHG emissions was determined from the results obtained. Electricity consumption contributed to the highest GHG emissions within the supply chains measured, followed by refrigeration gas leakage and disposal of unused fish portions. Potential cleaner production strategies (CPS) to reduce these impacts included installing solar panels, recycling the waste, good housekeeping in refrigeration equipment maintenance, and input substitution of refrigeration gas. The results show a combination of these strategies have the potential to reduce up to 35% of the total GHG emissions from fillet harvest, processing and retail

Michigan State Fight Song

https://digitalcommons.library.umaine.edu/mmb-vp-copyright/6606/thumbnail.jp

The relationship between personality type preferences and levels of coping resources among cardiac rehabilitation participants at the University of Wisconsin-La Crosse

This study was designed to determine the relationships between personality type preference as measured by the Myers-Briggs Type Indicator (MBTI), and the self-reported coping resources scores as measured by the Coping Resource Inventory (CRI). Data were collected from 31 volunteers of the Cardiac Rehabilitation Program at the University of isc cons in-La Crosse. Each volunteer completed both the MBTI and the CRI. T-test, stepwise regression, and canonical correlation were used to analyze the research hypotheses. Particular attention was focused on anger for which the researcher Aeveloped a subscale from the CRI questions. The T-test results indicated that the mean score for anger did not differ significantly from the three other types; intuitive-perceiving, intuitivejudging, and sensing-perceiving combined. The stepwise regression procedure was used to determine whether anger could be predicted by the variables of the MBTI. There was a significant inverse correlation between anger and sensing-intuitive (SN) score and anger and extrovertintrovert (EI) score. As the score for anger increases, the SN continuum goes from S to N (p>.0085). Also, as the score for anger increases the EI continuum moves from I to E (p>.0082). The .05 alpha level was the accepted probability level for rejection of the null hypothesis. The canonical correlations between the MBTI variables and the variables of the CRI were moderate, the largest being .4952 between social and EI score, and -.4644 between anger and SN score. The first canonical correlation was .6671, which was substantially larger than any of the between-set correlations. The probability level for the null hypothesis that all the canonical correlations in the population was .I305 so no firm conclusion was drawn. The remaining canonical correlations seemed to indicate only a potential for a positive correlation. Results of the data analysis indicate there was a relationship between anger and the sensing and introvert type preferences