ABSTRACT
Background: Data mining [DM] is an approach used in extracting valuable information from environmental processes. This research depicts a DM approach used in extracting some information from influent and effluent wastewater characteristic data of a waste stabilization pond [WSP] in Birjand, a city in Eastern Iran
Methods: Multiple regression [MR] and neural network [NN] models were examined using influent characteristics [pH, Biochemical oxygen demand [BOD[5]], temperature, chemical oxygen demand [COD], total suspended solids [TSS], total dissolved solid [TDS], electrical conductivity [EC] and turbidity] as the regression input vectors. Models were adjusted to input attributes, effluent BOD[5] [BODout] and COD [CODout]. The models performances were estimated by 10-fold external cross-validation. An internal 5-fold cross-validation was also used for the training data set in NN model. The models were compared using regression error characteristic [REC] plot and other statistical measures such as relative absolute error [RAE]. Sensitivity analysis was also applied to extract useful knowledge from NN model
Results: NN models [with RAE = 78.71 +/- 1.16 for BODout and 83.67 +/- 1.35 for CODout] and MR models [with RAE = 84.40% +/- 1.07 for BODout and 88.07 +/- 0.80 for CODout] indicate different performances and the former was better [P < 0.05] for the prediction of both effluent BOD5 and COD parameters. For the prediction of CODout the NN model with hidden layer size [H] = 4 and decay factor = 0.75 +/- 0.03 presented the best predictive results. For BODout the H and decay factor were found to be 4 and 0.73 +/- 0.03, respectively. TDS was found as the most descriptive influent wastewater characteristics for the prediction of the WSP performance. The REC plots confirmed the NN model performance superiority for both BOD and COD effluent prediction
Conclusion: Modeling the performance of WSP systems using NN models along with sensitivity analysis can offer better understanding on exploring the most significant parameters for the prediction of system performance. The findings of this study could build the foundation for prospective work on the characterization of WSP operations and optimization of their performances with a view to conducting statistical approaches
ABSTRACT
Introduction: Countries around the world are looking for an appropriate, stable, and affordable replacement for the natural energies. Therefore, the waste is considered as an available resource to produce energy, which by controlling, its effects on the environment could be minimized
Materials and Methods: To conduct this review article, the scientific data related to the topic were gathered from scientific databases such as Google Scholar, PubMed, Elsevier, Scopus, Springer, Magiran, and SID using waste to energy, Biogas, Incinerator, Landfill, and Pyrolysis as the keywords. In addition, 53 articles were used for this research [from 1993 until 2016]
Results: The results indicated that from a technical point of view, according to Iran's current environment and the properties of the produced waste, most methods mentioned in the study are applicable. However, the important issue is to choose the best technologies with the best functionality in Iran, based on the composition of the municipal solid waste, proved technologies, and the municipal solid waste management strategies
Conclusion: This study recommends construction of incineration plants with an appropriate location for processing municipal, household, and industrial hazardous wastes, as well as energy recovery. In addition, promoting application of household biogas reservoirs in villages and use of pyrolysis for some industries to converse industrial waste into fuel, are further suggested
ABSTRACT
Main function of corpus luteum is progesterone synthesis that is significantly accompanied with an increase in levels of mRNA encoding of steroidogenic enzymes known as luteal markers. This study was designed to evaluate effects of lithium chloride on the release of steroid hormones and steroidogenic enzymes in gonadotropin-stimulated rats. Immature 23 days old Wistar rats were divided into 10 groups; each group comprised of 8 rats, and induced with single injection of pregnant mare's serum gonadotrophin [PMSG] and followed by single injection of human chorionic gonadotropin [hCG]. Then, rats were given lithium chloride [LiCl] or saline at 12 hours post-hCG injection. Ovaries were collected in 4-hour interval from 8-24 hour post-hCG injection. Expression pattern of steroidogenic acute regulatory protein [StAR], side-chain cleavage cytochrome P450 [P450scc] and 3beta-hydroxysteroid dehydrogenase [3beta-HSD] genes were determined by semi-quantitative RT-PCR. In addition, serum levels of progesterone and 17beta-estradiol were measured by ELISA. Our results showed that hCG stimulation of progesterone was markedly diminished and transcript levels of key steroidogenic enzymes were altered in the hormone-stimulated rats following LiCl treatment. These results suggest that critical steps in the function of corpus luteum are disrupted by lithium. It is concluded that LiCl is an effective factor for suppressing of steroid genes expression