Environmental Research Institute of Jahad Daneshgahi

Iran

Environmental Research Institute of Jahad Daneshgahi

Iran

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Rakhshaee R.,Islamic Azad University at Rasht | Panahandeh M.,Environmental Research Institute of Jahad Daneshgahi
Journal of Hazardous Materials | Year: 2011

The removal of methylene blue (MB) as a cationic dye from aqueous solution by the stabilized Fe3O4 nano-particles with the extracted pectin from apple waste (FN-PA) increased due to using the cross-linked forms of the bound pectin on the nano-particles surface by glutaraldehyde (FN-PAG) and adipic acid (FN-PAA) as the cross-linking agents. This increase happened in spite of binding some of the adsorbent functional groups of pectin with nano-particles. It can be due to the local concentrate of other free functional groups after connecting with nano-scale particles. Thermodynamic studies showed that the adsorption equilibrium constant and the maximum adsorption capacities increased with increasing temperature for all of the nano-bioparticles. The kinetic followed the second-order models with the highest rate constants viz. 16.23, 19.76 and 23.04 (×10-3g/mgmin) by FN-PAA. The adsorption force arrangement of MB by these nano-biosorbents regarding their activation energy was obtained as: FN-PAA>FN-PAG>FN-PA. © 2011 Elsevier B.V.


Khoshhal A.,Islamic Azad University at Darab | Dakhel A.A.,Environmental Research Institute of Jahad Daneshgahi | Etemadi A.,Ferdowsi University of Mashhad | Zereshki S.,Kermanshah University of Technology
Journal of Food Process Engineering | Year: 2010

Artificial neural network (ANN) modeling and several mathematical models were applied to predict the moisture ratio in an apple drying process. Four drying mathematical models were fitted to the data obtained from eight drying runs and the most accurate model was selected. Two sets of ANN modeling were also performed. In the first set, the data obtained from each pilot were modeled individually to compare the ANN predictions with the best mathematical model. In the second set of ANN modeling, the simultaneous effect of all the four input parameters including air velocity, air temperature, the thickness of apple slices and drying time was investigated. The results showed that the ANN predictions were more accurate in comparison with the best fitted mathematical model. In addition, none of the mathematical models are able to predict the effect of the four input parameters simultaneously, while the presented ANN model predicts this effect with a good precision. © 2009 Wiley Periodicals, Inc.


Nassaj Hosseini S.M.,Environmental Research Institute of Jahad Daneshgahi | Nassaj Hosseini S.M.,Tarbiat Modares University | Shams-Bakhsh M.,Tarbiat Modares University | Mehrvar M.,Ferdowsi University of Mashhad | Salmanian A.H.,Iran National Institute of Genetic Engineering and Biotechnology
Journal of Agricultural Science and Technology | Year: 2013

To study molecular evolutionary characteristics and genetics of beet necrotic yellow vein virus (BNYVV) isolates population from Iran, nucleotide sequences of p25 and coat protein (CP) were determined and the amino acids sequences thus deduced were analyzed using phylogenetic and population genetics methods. A survey of BNYVV in Iran indicated the infection of 288 collected samples out of 392 samples in most beet growing areas and that most of the isolates (92%) were of the A-type and the rest of isolates (8%) were P-type. Our molecular evolutionary analysis showed that CP was highly conserved but allowed to assign all isolates to three distinct groups. Different parts of p25 coding regions were under different evolutionary constraints. The most positive selection was detected at the position 68, the second amino acid of the tetrad motif. Iranian isolates were found to cluster with European isolates into three distinct clusters based on p25 sequences. Population genetics analysis revealed that BNYVV populations have low differentiation (Kt= 3.97145) and low diversity (πT= 0.006, Hd= 0.860) with frequent gene flow indicating lack of phylogeographic structure between populations.


Abedinzadeh N.,Environmental Research Institute of Jahad Daneshgahi | Abedinzadeh F.,Islamic Azad University at Tehran | Abedi T.,Environmental Research Institute of Jahad Daneshgahi
Journal of Environmental Studies | Year: 2011

Introduction. Increasing growth of population and consequently increasing production of waste and special concerns about the loss of resources, lead experts to consider solid waste management issue on their agenda. Municipal solid waste management depends on factors such as residue production, collection, transportation, landfilling and recycling. So the scopes of management organization within these categories are very broad and variable. Such an organization cannot be managed only on the basis of the executive management experiences. There will be no way but the application of strategic management. One of the most appropriate techniques of planning and analysis is. In the present study, SWOT matrix technique has been used in order to provide proper strategies for waste management in the Rasht metropolitan with a waste production rate of 560 tons per day, Materials and methods This study deals with the investigation and identification of environmental factors including internal factors, that is the strengths and weaknesses and external factor, opportunities and threats. To achieve this, variables of internal and external environments of municipal waste management were to be identified. All strategic factors were evaluated and the importance priorities of factors were diagnosed and classified. Tables 1 to 5 show SWOT matrix of solid waste management in Rasht. "Table Present" "Table Present" To assess internal and external strategic factors, IFE (Internal Factors) and EFE (External Factor) matrices are used. In the matrices, for each of these factors one mark was considered based on their importance for solid waste management of Rasht. Thus, the highest score in internal and external matrices are 20 and 19 respectively. In the next step a weight coefficient between zero and one was assigned to each factor. In this study normalizing has been used for weighting. The coefficient given to each factor indicates its relative importance in success. Then a score between 1 and 4 is awarded to the current situation of each factor. If the organization management seeks to reduce weaknesses or threats, the high score on the weakness or threat will be allocated and the strengths and opportunities will be compared in order not to get low scores. To calculate the weighted score, the score of each row of internal and external factors of organization was normalized by multiplying the weight and inserting them in a new column. In this stage, the sum of weighted scores is calculated. If the IFE waste management score is less than 2.5, this means that waste management in terms of internal factors is generally weak. Also, if the EFE waste management score is less than 2.5, confirms that waste management has not been working properly on the use of opportunities and confronting threats. After analyzing the results of internal and external factors, evaluating matrices and creating proposed strategies, to estimate scores for each category of strategies and their priorities, QSPM matrix (Quantitative Strategic Planning Matrix) is used. In QSPM for each internal and external factor involved in a successful organization, attractiveness scores (between 1 = no appeal to 4 = very attractive) are to be determined. Total scores on the next stage of appeal are calculated. The coefficients are to be multiplied to the attractiveness scores. Total attractiveness score indicates relative attractiveness of each of the strategies. These are obtained only with regard to the relevant internal and external factors. The more the total attractiveness score is, the more attractive the discussed strategy will be. Finally, total attractiveness score related to each column of the quantitative matrix is calculated. The method simultaneously evaluated different classified strategies and priorities. Discussion of results High scores indicate that the strategy is more attractive. The average score of the internal factor matrix (IFE) of waste management in Rasht is determined to be less than 2.5 (2.35). This shows that the current solid waste management system in Rasht acts weakly from the internal factor aspect. While the average score of EFE matrix is 2.83. This indicates that solid waste management system is working acceptably in using the opportunities and confronting threats. In this phase of the research, strategies defined by internal and external factors of waste management in Rasht, have been classified into 10 strategies and have been applied to the quantitative strategic planning matrix to evaluate the attractiveness in classified priorities. These strategies include: St1- Laws and regulations regarding compliance and reduction of waste and separation at the source of production St2- Cultural activities and promoting public training to change the consumption patterns St3- Providing executive infrastructure of waste management economically St4- Transferring solid waste collection and recycling to the private sector St5- promoting waste collection technology St6-training municipality personnel for safety precautions and personal hygiene St7- implementing the provisions of waste management activities St8- Using appropriate methods of reducing pollutants in the landfill St9- Using advanced technology and skilled manpower to perform recovery processes St 10- Promoting the culture of recycling and advertising on the use of recycled products Conclusion The results of the quantitative strategic planning matrices show that among the above developed strategies, the highest attractiveness is related to "implementing the provision of waste management activities". The strategy score is 5.33. The lowest attractiveness is related to "using appropriate methods of reducing pollutants in the landfill" with a score of 1.04.

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