Effective use of WebCT in a problem-based learning course for a dual mode delivery

As part of a radical curriculum change, the Faculty of Engineering and Surveying at the University of Southern Queensland (USQ) introduced a strand of four problem-based learning (PBL) courses in 2002 [1]. While the first of these courses concentrates on building team skills, the second in the strand, Engineering Problem Solving 2 (ENG2102), introduces statistical analysis, basic physics concepts and elements of GIS and mapping as part of the technical content. The annual enrolment in this course is about 250 including over 100 students studying this course externally. One of the important factors to be considered in the design and delivery of such course is to provide an effective e-learning system considering that a significant number of the students study through the distance mode

Remote-sensing constraints on South America fire traits by Bayesian fusion of atmospheric and surface data

Satellite observations reveal substantial burning during the 2007 and 2010 tropical South America fire season, with both years exhibiting similar total burned area. However, 2010 CO fire emissions, based on satellite CO concentration measurements, were substantially lower (−28%), despite the once‐in‐a‐century drought in 2010. We use Bayesian inference with satellite measurements of CH_4 and CO concentrations and burned area to quantify shifts in combustion characteristics in 2010 relative to 2007. We find an 88% probability in reduced combusted biomass density associated with the 2010 fires and an 82% probability of lower fire carbon losses in 2010 relative to 2007. Higher combustion efficiency was a smaller contributing factor to the reduced 2010 CO emissions. The reduction in combusted biomass density is consistent with a reduction (4–6%) in Global Ozone Monitoring Experiment 2 solar‐induced fluorescence (a proxy for gross primary production) during the preceding months and a potential reduction in biomass (≤8.3%) due to repeat fires

Detection of fossil fuel emission trends in the presence of natural carbon cycle variability

Atmospheric CO₂ observations have the potential to monitor regional fossil fuel emission (FFCO₂) changes to support carbon mitigation efforts such as the Paris Accord, but they must contend with the confounding impacts of the natural carbon cycle. Here, we quantify trend detection time and magnitude in gridded total CO₂ fluxes—the sum of FFCO₂ and natural carbon fluxes—under an idealized assumption that monthly total CO₂ fluxes can be perfectly resolved at a 2°×2° resolution. Using Coupled Model Intercomparison Project 5 (CMIP5) 'business-as-usual' emission scenarios to represent FFCO₂ and simulated net biome exchange (NBE) to represent natural carbon fluxes, we find that trend detection time for the total CO₂ fluxes at such a resolution has a median of 10 years across the globe, with significant spatial variability depending on FFCO₂ magnitude and NBE variability. Differences between trends in the total CO₂ fluxes and the underlying FFCO₂ component highlight the role of natural carbon cycle variability in modulating regional detection of FFCO₂ emission trends using CO₂ observations alone, particularly in the tropics and subtropics where mega-cities with large populations are developing rapidly. Using CO₂ estimates alone at such a spatiotemporal resolution can only quantify fossil fuel trends in a few places—mostly limited to arid regions. For instance, in the Middle East, FFCO₂ can explain more than 75% of the total CO₂ trends in ~70% of the grids, but only ~20% of grids in China can meet such criteria. Only a third of the 25 megacities we analyze here show total CO₂ trends that are primarily explained (>75%) by FFCO₂. Our analysis provides a theoretical baseline at a global scale for the design of regional FFCO₂ monitoring networks and underscores the importance of estimating biospheric interannual variability to improve the accuracy of FFCO₂ trend monitoring. We envision that this can be achieved with a fully integrated carbon cycle assimilation system with explicit constraints on FFCO₂ and NBE, respectively

Asian monsoon hydrometeorology from TES and SCIAMACHY water vapor isotope measurements and LMDZ simulations: Implications for speleothem climate record interpretation

International audienceObservations show that heavy oxygen isotope composition in precipitation (delta O-18(p)) increases from coastal southeastern (SE) China to interior northwestern (NW) China during the wet season, contradicting expectations from simple Rayleigh distillation theory. Here we employ stable isotopes of precipitation and vapor from satellite measurements and climate model simulations to characterize the moisture processes that control Asian monsoon precipitation and relate these processes to speleothem paleoclimate records. We find that delta O-18(p) is low over SE China as a result of local and upstream condensation and that delta O-18(p) is high over NW China because of evaporative enrichment of O-18 as raindrops fall through dry air. We show that delta O-18(p) at cave sites over southern China is weakly correlated with upstream precipitation in the core of the Indian monsoon region rather than local precipitation, but it is well-correlated with the delta O-18(p) over large areas of southern and central China, consistent with coherent speleothem delta O-18(p) variations over different parts of China. Previous studies have documented high correlations between speleothem delta O-18(p) and millennial timescale climate forcings, and we suggest that the high correlation between insolation and speleothem delta O-18(p) in southern China reflects the variations of hydrologic processes over the Indian monsoon region on millennial and orbital timescales. The delta O-18(p) in the drier part (north of similar to 30 degrees N) of China, on the other hand, has consistently negative correlations with local precipitation and may capture local hydrologic processes related to changes in the extent of the Hadley circulation

El Niño, the 2006 Indonesian peat fires, and the distribution of atmospheric methane

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110818/1/grl50937.pd

The dangers of sublethal carvacrol exposure: increases in virulence of Bacillus cereus during endophthalmitis

Bacillus cereus can cause endophthalmitis through secretion of virulence factors, including hemolysin BL (Hbl) and nonhemolytic entertoxin (Nhe). Carvacrol is an extract from oregano oil, with potential for curtailing B. cereus endophthalmitis, due to antimicrobial and anti-inflammatory qualities. However, sublethal levels of carvacrol increases B. cereus virulence. The goal of this study was to investigate the increase in B. cereus virulence potential in response stress induced by a subinhibitory concentration (SIC) of carvacrol. Enterotoxin production and tissue damage were examined during ocular infections in vitro and in vivo. We hypothesized that the SIC of carvacrol would significantly increase toxin production in B. cereus without progressing systemically. RT-PCR determined SIC carvacrol-treated B. cereus had significantly higher hblC and nheA mRNA expression levels than controls in vitro. ELISA and RPLA analysis revealed a 46.8% and 50% increase in NheA and HblC toxin levels, respectively, in SIC-treated cultures. Caenorhabditis elegans-fed SIC carvacrol-treated B. cereus had a significantly higher mean mortality rate than nematodes fed untreated B. cereus. Significantly higher TNF-α levels were observed in SIC carvacrol-treated B. cereus mice compared to other treatment groups except for mice infected with B. cereus alone. Significantly higher IL-6 levels were also found in SIC-B. cereus mice. Histological analysis using Rose-Bengal and DAPI determined that the eyes of mice infected with SIC carvacrol-treated B. cereus had significantly more damage than eyes treated with B. cereus alone. The SIC of carvacrol increased B. cereus virulence in vitro and in vivo, with a mild systemic infection noted

Melodrama and meaning

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