The effect of humic acid in chronic deoxynivalenol intoxication

Environmental Science and Pollution Research - The most common mycotoxin found in European foodstuffs, especially unprocessed grains, is deoxynivalenol (DON), which inhibits proteosynthesis and...     

Dimethoate induces genotoxicity as a result of oxidative stress: in vivo and in vitro studies

Environmental Science and Pollution Research - Dimethoate ([O,O-dimethyl S-(N-methylcarbamoylmethyl) phosphorodithioate]) is an organophosphate insecticide and acaricide widely used for...     

Economic performance of Indonesia amidst CO2 emissions and agriculture: a time series analysis

Environmental Science and Pollution Research - To minimize the awful situation confronting the entire globe, the global warming danger has raised the intensity of consciousness from all areas of...     

The influences of renewable electricity generation,technological innovation,financial development,and economic growth on ecological footprints in ASEAN-5 countries

Environmental Science and Pollution Research - The Southeast Asian countries have experienced significant degrees of economic growth over the years but have not managed to safeguard their...     

Norovirus GII.Pe Genotype: Tracking a Foodborne Outbreak on a Cruise Ship Through Molecular Epidemiology,Brazil, 2014

Norovirus (NoV) is recognized as the most common cause of foodborne outbreaks. In 2014, an outbreak of acute gastroenteritis occurred on a cruise ship in Brazil, and NoV became the suspected etiology. Here we present the molecular identification of the NoV strains and the use of sequence analysis to determine modes of virus transmission. Food (cream cheese, tuna salad, grilled fish, orange mousse, and vegetables soup) and clinical samples were analyzed by ELISA, conventional RT-PCR, qRT-PCR, and sequencing. Genogroup GII NoV was identified by ELISA and conventional RT-PCR in fecal samples from 5 of 12 patients tested (41.7%), and in the orange mousse food sample by conventional RT-PCR and qRT-PCR. Two fecal GII NoV samples and the orange mousse GII NoV sample were successfully genotyped as GII.Pe (ORF 1), revealed 98.0–98.8% identities among them, and shared phylogenetically distinct cluster. Establishing the source of a NoV outbreak can be a challenging task. In this report, the molecular analysis of the partial RdRp NoV gene provided a powerful tool for genotyping (GII.Pe) and tracking of outbreak-related samples. In addition, the same fast and simple extraction methods applied to clinical samples could be successfully used for complex food matrices, and have the potential to be introduced in routine laboratories for screening foods for presence of NoV.     

Experience,but not distance,influences the recruitment precision in the stingless bee <Emphasis Type="Italic">Scaptotrigona mexicana</Emphasis>

Recruitment precision, i.e. the proportion of recruits that reach an advertised food source, is a crucial adaptation of social bees to their environment. Studies with honeybees showed that recruitment precision is not a fixed feature, but it may be enhanced by factors like experience and distance. However, little is known regarding the recruitment precision of stingless bees. Hence, in this study, we examined the effects of experience and spatial distance on the precision of the food communication system of the stingless bee Scaptotrigona mexicana. We conducted the experiments by training bees to a three-dimensional artificial patch at several distances from the colony. We recorded the choices of individual recruited foragers, either being newcomers (foragers without experience with the advertised food source) or experienced (foragers that had previously visited the feeder). We found that the average precision of newcomers (95.6 ± 2.61%) was significantly higher than that of experienced bees (80.2 ± 1.12%). While this might seem counter-intuitive on first sight, this “loss” of precision can be explained by the tendency of experienced recruits to explore nearby areas to find new rewarding food sources after they had initially learned the exact location of the food source. Increasing the distance from the colony had no significant effect on the precision of the foraging bees. Thus, our data show that experience, but not the distance of the food source, affected the patch precision of S. mexicana foragers.     

Driver education and graduated licensing in North America: past, present, and future

PROBLEM: A stated objective of driver education in North America is to produce safer drivers, typically defined as drivers less likely to crash. This paper examines the extent to which driver education has achieved this objective independently as well as the extent to which such programs can support the success of graduated licensing in reducing young driver crashes. In so doing, it discusses past experiences, recent developments, and the future direction of driver education and training in relation to graduated driver licensing. METHOD: Literature review and synthesis. RESULTS: Driver education programs have yet to demonstrate consistent attainment of their safety objectives. Moreover, they have not been found to enhance the safety effectiveness of graduated licensing programs--indeed, some practices, for example, "time discounts" for driver education have actually had a detrimental effect on teen safety. DISCUSSION: Despite its disappointing safety record to date, it is important not to abandon driver education. In particular, there are opportunities to improve driver education so that it achieves its safety objectives, and ensure that programs in the future complement graduated driver licensing and contribute to its overall safety benefits. Current and future efforts to improve driver education and better integrate it with graduated licensing programs, however, need to be rigorously evaluated to determine what does and does not work to reduce young driver crashes, and as importantly, to understand why this is the case. IMPACT ON INDUSTRY: Improved driver education integrated with graduated driver licensing has potential safety benefits.     

Effect of sulfate on the methanogenic activity of a bacterial culture from a brewery wastewater during glucose degradation

The maximum specific methanogenic activity （SMA） of a sludge originating from a brewery wastewater treatment plant on the degradation of glucose was investigated at various levels of sulfate on a specific loading basis. Batch experiments were conducted in serum bottles at pH 7 and 35℃. A comparison of the values indicates that the SMA of this mixed culture was increased and reached its highest level of 0.128 g CH4 gas COD/（g VSS.d） when biomass was in contact with sulfate at a ratio of 1：0.114 by weight.     

Modeling Large Fire Frequency and Burned Area in Canadian Terrestrial Ecosystems with Poisson Models

Large wildland fires are major disturbances that strongly influence the carbon cycling and vegetation dynamics of Canadian boreal ecosystems. Although large wildland fires have recently received much scrutiny in scientific study, it is still a challenge for researchers to predict large fire frequency and burned area. Here, we use monthly climate and elevation data to quantify the frequency of large fires using a Poisson model, and we calculate the probability of burned area exceeding a certain size using a compound Poisson process. We find that the Poisson model simulates large fire occurrence well during the fire season (May through August) using monthly climate, and the threshold probability calculated by the compound Poisson model agrees well with historical records. Threshold probabilities are significantly different among different Canadian ecozones, with the Boreal Shield ecozone always showing the highest probability. The fire prediction model described in this study and the derived information will facilitate future quantification of fire risks and help improve fire management in the region.     

Assessment of Spatiotemporal Varying Relationships Between Rainfall,Land Cover and Surface Water Area Using Geographically Weighted Regression

Traditional regression techniques such as ordinary least squares (OLS) are often unable to accurately model spatially varying data and may ignore or hide local variations in model coefficients. A relatively new technique, geographically weighted regression (GWR) has been shown to greatly improve model performance compared to OLS in terms of higher R ² and lower corrected Akaike information criterion (AIC_C). GWR models have the potential to improve reliabilities of the identified relationships by reducing spatial autocorrelations and by accounting for local variations and spatial non-stationarity between dependent and independent variables. In this study, GWR was used to examine the relationship between land cover, rainfall and surface water habitat in 149 sub-catchments in a predominately agricultural region covering 2.6 million ha in southeast Australia. The application of the GWR models revealed that the relationships between land cover, rainfall and surface water habitat display significant spatial non-stationarity. GWR showed improvements over analogous OLS models in terms of higher R ² and lower AIC_C. The increased explanatory power of GWR was confirmed by the results of an approximate likelihood ratio test, which showed statistically significant improvements over analogous OLS models. The models suggest that the amount of surface water area in the landscape is related to anthropogenic drainage practices enhancing runoff to facilitate intensive agriculture and increased plantation forestry. However, with some key variables not present in our analysis, the strength of this relationship could not be qualified. GWR techniques have the potential to serve as a useful tool for environmental research and management across a broad range of scales for the investigation of spatially varying relationships.