Identification of periodic droughts can provide a scientific tool for predicting the occurrence of this environmental risk. One of the most important methods that can be used for detection of periodic droughts is the SPECTRAL ANALYSIS or frequency-domain ANALYSIS. The purpose of this study is to detect the periodic behavior of Iran’ s monthly droughts. To this aim, use has been made of the monthly rainfall statistics of 41 synoptic stations for a period of 31 years (1983– 2013) obtained from the IR of Iran Meteorological Organization (IRIMO). First, to identify considerable differences in droughts, the “ effective drought index” (EDI) was employed. Assigning a numerical value to each rainfall event on a monthly time scale is the main objective of the EDI in order to compare the areas with different climates based on it. Then the SPECTRAL ANALYSIS by Fourier transform was used to identify the dominant available periods in the stations’ drought time series. In this ANALYSIS, Radix-2 Fast Fourier Transform was used. Since Fourier transform leads to difficulties in the SPECTRAL ANALYSIS of non-stationary series, first the stationary condition of the EDI monthly time series was investigated for all of the 41 stations used in this study. In those stations with a non-stationary condition, the Box– Cox procedure was applied to make them stationary. The results were classified into five areas. The results showed that the dominant periods in the time series of Iran’ s droughts vary greatly from periods of 2 to 30 years. In addition to the dominant short-term periods, droughts in the northwest of Iran have two dominant long-term periods of 10 and 30 years. Droughts in the southern coast of the Caspian Sea have shorter periodicities. So with the exception of the two stations of Ramsar and Ardebil with the periodicities of 30 and 15 years, the other stations have periods of less than 10 years. The dominant periods in most stations in the northern districts of central Iran are short-term ones, and the longest periodicity in this area is 15 years. The southern districts of the central Iran have a more consistent SPECTRAL behavior. In this area, the dominant period with the highest power is the period of 30 years. All of the stations in this area with the exception of Mashhad station have a 30-year period in their first three components. The 10-year period, as the second dominant period, can also be seen in half of the stations in this area. The southeast area does not exhibit any specific behavior for the dominant periods. The longest periodicity in Chabahar station is a 10-year period. The two stations in Zabol and Iranshahr have shown the longest period of 30 years and the long-term period seen in Zahedan is a 15-year one. In addition to these long-term periods, a period of 2. 5 to 3 years can play the role of the dominant short-term period in this area. In general, for the long-term behavior, the two periods of 10 and 30 years can be considered as being the dominant periods across Iran. Among the long-term periods, the frequency of occurrence of these two periods is maximum in the first component and reduces in the other two components. In the third component, the minimum frequency of occurrence of these two periods is seen.

Background: Betatrophin, a novel secretory protein from liver and fatty tissues, is believed to be involved in lipid and glucose metabolism. However, its precise physiological role remains unclear. Here, we report the cloning, expression, and purification steps of mouse betatrophin in a prokaryotic system, followed by its structural ANALYSIS. Methods: Specific cloning primers were used to amplify the coding sequence of mouse liver betatrophin. The product was cloned into pET28 and expressed in E. coli BL21 (DE3) cells. The suitability of the refolding procedure was assessed by determining secondary structures of the initial and refolded proteins using circular dichroism spectroscopy. Results: The polymerase chain reaction resulted in a 549 bp nucleotide sequence, encoding a 183 amino acid polypeptide, with an apparent molecular weight of 21 kDa, which was expressed in an inclusion body. Following an optimization and refolding procedure, the recombinant protein was purified by anion exchange and metal affinity chromatography. CD spectra revealed that the refolded protein has suitable configuration. Conclusion: We believe that the produced betatrophin is suitable for further biochemical studies on glucose and lipid metabolism.

Nowadays, the maximum operation of groundwater resources has been achieved in Iran. Also, the majority of extractable water resources are utilized and the managing of water resources in the future is depended on more extracting of water resources. For better basin management, forecasting the groundwater depth fluctuations in particular in arid areas is more necessary. In this study, time series SPECTRAL ANALYSIS is used to forecast the groundwater depth fluctuations of Chamchamal plain. In this regard, the monthly groundwater depth time series during 1995 to 2009 years are used for calibration periods and the periodogram diagrams are depicted. Data periodicity is analyzed by using Fourier SPECTRAL ANALYSIS and the deterministic term of data periodicity is eliminated. In the next step, stationary and normality in the data are considered. After that, the different time series models are fitted for the prepared data and accuracy of them were assessed by Akaike (AIC) criterion. The results show that ARMA (2, 1), ARMA (1, 1), ARMA (1, 1) models are the best fitted models for the measured data in Bazanabad, Gheshlaghabad and Gavkol piezometers, respectively. Finally, the residuals stationarity assumption test is used to check for the correct diagnosis of the fitted pattern. In this study, the results represent the high performance and accuracy of the applied new approach to the time series SPECTRAL ANALYSIS for forecasting groundwater depth by application of the regression coefficient amount of 0. 78 and SI-Index of 4% to 14% of piezometers' data. Using SPECTRAL ANALYSIS, as has been provided in this study, is very useful for forecasting groundwater depth.

In this research the flow-precipitation fluctuations in 9 station in Dinevar basin were analyzed by SPECTRAL density functions and Autocorrelation Functions in the frequency and time domain. First fluctuations in the correlogram of each time series were analyzed. Then SPECTRAL density functions based on the Fourier series were used to check the time series in the frequency domain. In this regard, the Spectrum value of each flow and rainfall series was calculated and the periodogram of each series was produced. The Periodograms showed fluctuations in several frequencies. These were seasonal fluctuations with frequency 0.083 (return period of 12 months), short term fluctuations with frequency 0.25 (return period of 4 months), and midterm fluctuations with frequency 0.167 (return period of 4 months). Fluctuations were not observed for return period of 6 months in Precipitation data. Cross SPECTRAL ANALYSIS of data showed high match levels in frequencies 0.083 and 0.25. Also the estimated values of delay by cross SPECTRAL ANALYSIS for precipitation seasonal fluctuations (0.083) and its effect on the seasonal flow fluctuations was estimated as about 1.5 months. The delay was determinate as 0.4, 0.5, and 0.14 months for fluctuations with smaller return periods. According to the SPECTRAL ANALYSIS results for precipitation data in all stations, after removing the frequency and trends, a long term fluctuation (cycle) was observed in frequency 0.01 (100 months) that can be associated to the Wet and dry periods in this region.