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1
The diet of Indian flying-foxes (Pteropus giganteus) in urban habitats of Pakistan
100%
Mahmood- ul-Hassan M. , Gulraiz T. L. , Rana S. A. , Javid A.
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2010
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tom 12
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nr 2
EN
We studied the diet of the Indian flying fox (Pteropus giganteus) in Pakistan from March 2008 to February 2009 and found that the bats fed on 20 species belonging to 11 plant families. Of these, four families (Anacardiaceae, Bignonaceae, Malvaceae, and Sapotaceae) were identified from remnants of flower petals in food boluses while the remaining families (Annonaceae, Arecaceae, Ebenaceae, Meliaceae, Moraceae, Myrtaceae, and Sapindaceae) were identified from the seeds in the boluses and from guano samples. Plants in the family Moraceae (50.7%) comprised most of the bat's diet. Fruit of Ficus retusa (27.5%) and F. carica (23.0%) during winter, F. glomerata (30.9%) and F. religiosa (28.1%) during spring, Psidium guajava (19.6%), F. bengalensis (18.7%) and Diospyros peregrina (17.8%) during summer, and D. peregrina (71.9%) during autumn, were the most frequently identified items. The four seasonal diets varied significantly (χ2 = 435, d.f. = 18, P < 0.01). Results confirm that the ecological services rendered by P. giganteus, such as pollination and seed dispersal, outweigh its losses, such as damage to the ripe fruit. Hence, the species should not be regarded as a pest; rather efforts should be made to ensure its conservation.
2
Content available Artificial neural network (ANN) modeling of COD reduction from landfill leachate by the ultrasonic process
100%
Arabameri M. , Javid A. , Roudbari A.
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tom Vol. 43, nr 1
59--73
EN
In the study, the use of an artificial neural network (ANN) has been applied for the prediction of COD removal from landfill leachate by the ultrasonic process. The configuration of the backpropagation neural network giving the lowest mean square error (MSE) was a three-layer ANN with a tangent sigmoid transfer function (tansig) at a hidden layer with 14 neurons, linear transfer function (purelin) at the output layer and the Levenberg–Marquardt backpropagation training algorithm (LMA). The ANN predicted results are very close to the experimental data with the correlation coefficient (R2) of 0.992 and the MSE of 0.000331. The sensitivity analysis showed that all studied variables (contact time, pH, ultrasound frequency and power) have strong effect on COD removal. In addition, ultrasound power is the most influential parameter with relative importance of 25.8%. The results showed that modeling neural network could effectively predict COD removal from landfill leachate by ultrasonic process.
3
Content available Measurements of bioaerosols in the air around the facilities of waste collection and disposal
100%
Roodbari A. , Naddafi K. , Javid A.
Environment Protection Engineering
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2013
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tom Vol. 39, nr 4
105--112
EN
Exposure to bioaerosols at various stages of waste management system (collection, transfer and disposal) has been evaluated by recording of the bacterial and fungal concentrations in the air around these facilities. Regardless of the season, the total bacteria and total fungi were detected for all sampies, whereas the fungal genera were not. The bioaerosol concentrations measured in the waste collection bins were significantly higher than those of the transfer station and landfill site. The mean microbial concentrations at wastes container bins and in-operation trench exceeded the Iran outdoor bioaerosol guidelines (850 CFU/m3), thus suggesting the need for remedial action regarding microorganisms, in order to reduce the exposure at the wastes management system.
4
Content available An evaluation of water quality from Mojen River, by NSFWQI index
100%
Javid A. , Yaghmaeian K. , Abbasi E. , Roudbari A.
Journal of Ecological Engineering
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2014
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tom Vol. 15, nr 4
1--6
EN
Water quality index (WQI) is valuable and unique rating to depict the overall water quality status in a single term that is helpful for the selection of appropriate treatment technique to meet the concerned issues. The aim of the study was to evaluating water quality from Mojen River by Water Quality Index based on National Science Foundation (NSFWQI). For this purpose, samples were collected from stations at up, middle and downstream of Mojen River in Semnan province (the biggest river in region) in a 2 years interval of 2013-2014 years. Nine parameters namely Turbidity, Biochemical Oxygen Demand, Dissolved Oxygen, Fecal Coliform, nitrate, pH, temperature, total solids and total phosphate were considered to compute the index. Our findings highlighted the deterioration of water quality in the river due to industrialization and human activities. According to NSFWQI, the best condition was recorded in the Dark haniab (Upstream) and the worst condition concerned the Pole (Midstream).
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Total anthocyanin, flavonoid, polyphenol and tannin contents of seven pomegranate cultivars grown in Iran
75%
Mottaghipisheh J. , Ayanmanesh M. , Babadayei-Samani R. , Javid A. , Sanaeifard M. , Vitalini S. , Iriti M.
Acta Scientiarum Polonorum. Technologia Alimentaria
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2018
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tom 17
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nr 3
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