Assessing Storm Water Detention Systems Treating Road Runoff with an Artificial Neural Network Predicting Fecal Indicator Organisms

This paper examines whether multiple regression analysis and neural network models can be applied successfully for the indirect prediction of the runoff treatment performance with water quality indicator variables in an experimental storm water detention system rig. Five biologically mature experimental storm water detention systems with different designs treating concentrated gully pot liquor (spiked with dog droppings) were assessed. The systems were located on The King’s Buildings campus at The University of Edinburgh and were monitored for a period of 18 months. Multiple regression analyses indicated a relatively successful prediction of the biochemical oxygen demand and total suspended solids for most systems, but due to a relatively weak correlation between the predictors and both microbial indicators, multiple regression analyses were not applied for the prediction of intestinal enterococci and total coliform colony-forming units. However, artificial neural network models predicted microbial counts relatively well for most detention systems.     

Correction to: Droplet-vitrification cryotherapy and thermotherapy as efficient tools for the eradication of apple chlorotic leaf spot virus and apple stem grooving virus from virus-infected quince in vitro cultures

European Journal of Plant Pathology -     

An evaluation of harvesting costs in present and planned operations: case study—Waston District of Mazandaran Wood and Paper Industries

Amongst all forest utilization phases, harvesting plays a key role as the beginning phase of the utilization cycle and has a significant effect on the following phases.In this research, in order to examine the reduction of costs with respect to present and planned operations, the starting time of the harvesting or cutting phase and work flow were recorded. The starting time of each phase of the entire operation was recorded as well. Before harvesting the marked tree, the appropriate felling direction was determined and the azimuth of the correct direction was taken.The results indicate that there was not a meaningful relationship between the differences in direction of a leaning tree compared with the felling direction. However, there was a significant relationship between the difference of the defined and felling direction and the difference in tree leaning and defined direction. The same trend was observed between tree leaning and felling directions and tree leaning and defined directions. On the other hand,there was no significant relationship between tree leaning and felling directions and the defined and tree felling directions. In addition, this research shows that with an increase in tree volume, the time for tree cutting rose.Furthermore, when the difference of tree leaning and felling direction decreased, the time to cut the tree declined.The regression equation is Y = 168.9–0.14(the difference between tree leaning and felling direction) + 0.7(volume).     

Responses of Four Rice Varieties to Elevated CO2 and Different Salinity Levels

This study was carried out in 2014 at Isfahan University of Technology, Iran, to evaluate the responses of four rice varieties(Neda, Deylamani, Shiroudi and Domsorkh) to ambient(360 ± 50 μmol/mol) and elevated(700 ± 50 μmol/mol) air carbon dioxide(CO_2) concentrations under four salinity levels(0, 30, 60 and 90 mmol/L Na Cl). There was significant variation among rice varieties in response to elevated CO_2 concentration under the four salinity levels. Under non-saline condition, elevated CO_2 increased the dry weight of Neda, Deylamani and Domsorkh by 8%, 50% and 8%, respectively, but reversely decreased that of Shiroudi by 34%. Increasing CO_2 concentration significantly reduced the negative effects of salinity on Shiroudi, but these effects were even increased in Deylamani and Domsorkh under all the salinity levels and in Neda only under 30 and 60 mmol/L Na Cl. Significant correlations were established between plant dry weight, SPAD value and leaf area under both CO_2 levels. However, this trend was observed only at ambient CO_2 concentration in the presence of soluble carbohydrates. The results revealed the genotype and salinity dependence of the effects of CO_2 concentrations on the rice traits investigated.