List of forthcoming papers

List of forthcoming papers     

Analysis of stochastic characteristics of the Benue River flow process

Stochastic characteristics of the Benue River streamflow process are examined under conditions of data austerity. The streamflow process is investigated for trend, non-stationarity and seasonality for a time period of 26 years. Results of trend analyses with Mann-Kendall test show that there is no trend in the annual mean discharges. Monthly flow series examined with seasonal Kendall test indicate the presence of positive change in the trend for some months, especially the months of August, January, and February. For the stationarity test, daily and monthly flow series appear to be stationary whereas at 1%, 5%, and 10% significant levels, the stationarity alternative hypothesis is rejected for the annual flow series. Though monthly flow appears to be stationary going by this test, because of high seasonality, it could be said to exhibit periodic stationarity based on the seasonality analysis. The following conclusions are drawn： （1） There is seasonality in both the mean and variance with unimodal distribution. （2） Days with high mean also have high variance. （3） Skewness coefficients for the months within the dry season period are greater than those of the wet season period, and seasonal autocorrelations for streamflow during dry season are generally larger than those of the wet season. Precisely, they are significantly different for most of the months. （4） The autocorrelation functions estimated ＂over time＂ are greater in the absolute value for data that have not been deseasonalised but were initially normalised by logarithmic transformation only, while autocorrelation functions for i = 1, 2 365 estimated ＂over realisations＂ have their coefficients significantly different from other coefficients.     

Development in modeling cyclic loading of sands based on kinematic hardening

In this paper, there is presented an elastoplastic constitutive model to predict sandy soils behavior under monotonic and cyclic loadings. This model is based on an existing model (Cambou‐Jafari‐Sidoroff) that takes into account deviatoric and isotropic mechanisms of plasticity. The flow rule used in the deviatoric mechanism is non‐associated and a mixed hardening law controls the evolution of the yield surface. In this research the critical state surface and history surface, which separates the virgin and cyclic states in stress space, are defined. Kinematic hardening modulus and stress–dilatancy law for monotonic and cyclic loadings are effectively modified. With taking hardening modulus as a function of deviatoric and volumetric plastic strain and with defining the history surface and stress reversal, the model has the ability to predict the sandy soils' behavior. All of the model parameters have clear physical meanings and can be determined from usual laboratory tests. In order to validate the model, the results of homogeneous tests on Hostun and Toyoura sands are used. The results of validation show a good capability of the proposed model. Copyright © 2009 John Wiley & Sons, Ltd.     

New Criterion for Lunar Crescent Visibility

A new criterion for lunar crescent visibility has been established using 737 observations, almost half of them obtained by the Islamic Crescent Observation Project (ICOP). This criterion is based on two variables, viz. the topocentric arc of vision and the topocentric crescent width. The new model is able to predict the visibility of the lunar crescent both for naked eye and optically aided observations. From the database we found a Danjon limit of 6.4 degrees. Vice-President of “Crescents, Calendars and Mawaqeet Committee” of AUASS.     

Lee yang theory for cosmological many body problem

We study the phase transition in a gravitating system by analyzing grand canonical partition function as a function of complex fugacity. We extend the Yang-Lee theory to study phase transitions in the gravitational galaxy clustering of galaxies having a variety of masses. This generalizes our previous work based on the same theory for the single-component system to a multicomponent system. We find that galaxy clustering is sensitive to masses and number densities of individual galaxies at early stages while at later stages collective behavior of the particles is more pronounced. This validates our earlier work obtained from different considerations.     

A systematic review of strong gravitational lens modeling software

Despite expanding research activity in gravitational lens modeling, there is no particular software which is considered a standard. Much of the gravitational lens modeling software is written by individual investigators for their own use. Some gravitational lens modeling software is freely available for download but is widely variable with regard to ease of use and quality of documentation. This review of 13 software packages was undertaken to provide a single source of information. Gravitational lens models are classified as parametric models or non-parametric models, and can be further divided into research and educational software. Software used in research includes the GRAVLENS package (with both gravlens and lensmodel), Lenstool, LensPerfect, glafic, PixeLens, SimpLens, Lensview, and GRALE. In this review, GravLensHD, G-Lens, Gravitational Lensing, lens and MOWGLI are categorized as educational programs that are useful for demonstrating various aspects of lensing. Each of the 13 software packages is reviewed with regard to software features (installation, documentation, files provided, etc.) and lensing features (type of model, input data, output data, etc.) as well as a brief review of studies where they have been used. Recent studies have demonstrated the utility of strong gravitational lensing data for mass mapping, and suggest increased use of these techniques in the future. Coupled with the advent of greatly improved imaging, new approaches to modeling of strong gravitational lens systems are needed. This is the first systematic review of strong gravitational lens modeling software, providing investigators with a starting point for future software development to further advance gravitational lens modeling research.     

Woody species diversity and forest structure from lowland to montane forest in Hyrcanian forest ecoregion

Alborz Mountains host Caspian Hyrcanian forest ecoregion along the northern slopes and forest steppe ecoregion in highlands. Hyrcanian forest covers the southeastern part of Caucasus biodiversity hotspot and is of great biogeographic importance. Altitudinal pattern and correlation between woody species biodiversity (DIV), forest structure ((stem density (DEN), mean basal area (MBA) and mean height class (MHC)) and disturbance (DIS) were explored along 2,400 m altitudinal gradient in Hyrcanian relict forest, Central Alborz Mountains. Vegetation changes from lowland forest (LoF) to mid- altitude forest (MiF) and montane forest (MoF) in this area. The altitudinal gradient was divided into twelve 200 m elevational belts. Point centered quarter method (PCQM) with 96 sampling points and 83 vegetation samples by plot method (PM) were used to record field data. Shannon-Wiener index and Pearson coefficient were used for diversity and correlation analysis. The results showed that DEN decreased linearly, MBA and MHC showed relatively hump shaped and DIS showed a reverse hump shaped pattern of change along altitudinal gradient. Woody species diversity decreased non-steadily from LoF to MoF. Transitional vegetations of Carpinus-Fagus and Fagus-Quercus represented higher diversity of woody taxa compared to adjacent homogenous communities. Significant correlation was observed between altitude and all parameters: DEN with MBA, DIS and DIV; MBA with DIS; MHC with DIS along with DIV; and DIS with DIV at the study area scale. Surprisingly,correlation between studied parameters differed within each vegetation type. Altitude probably acts as a proxy for human and environmental driving forces in this area. Stability of warm and wet condition, season length, soil depth along with forest accessibility probably influences the altitudinal pattern of the studied parameters. Disturbance affects forest structure and consequently diversity; especially in lowlands. The obtained results recommend using both forest biodiversity and mensuration data in management process of forest ecosystems.     

Isolation, distribution and evaluation of cytotoxic and antioxidant activity of cultivable actinobacteria from the Oman Sea sediments

Screening bioactive natural products from bacteria is a determinative step in the drug discovery programs. The present study aim to isolate actinobacteria from the Oman Sea sediments for determining the effects of different culture media and treatments on the yield of the isolation process, and measure the DPPH radical scavenging and Artemia cytotoxic activity of culture extracts of the actinobacterial isolates. A total of 290 actinobacterial isolates were collected from 14 sediment samples. Heat treatment(40.68%) and M_4 medium(29.31%) exhibited the maximum isolation rates of actinobacteria. Streptomyces isolates were dominantly distributed in all of the investigated stations according to 16 S rRNA gene sequencing. The distribution pattern of Streptomyces followed a depth-dependent frequency trend, whereas the members of rare genera including Micromonospora, Nocardia Actinoplanes, Nocardiopsis, Saccharopolyspora and Crossiella were distributed in deeper stations. Approximately,25% of the examined isolates could scavenge 90% of 10~(–4) mol/L DPPH solutions at 1 250 μg/mL final concentration of their ethyl acetate culture extracts. Furthermore, the most potent extracts could scavenge DPPH radicals with IC50 ranges from 356.8 to 566.4 μg/mL. Brine shrimp cytotoxicity tests showed that 38.88% of the examined culture extracts exhibited LC_(50) lower than 1 000 μg/mL against the Artemia cells. Moreover, the most potent culture extracts exhibited LC_(50) range from 335.4 to 534.4 μg/mL. Phylogenetic analysis by 16 S rRNA gene sequence revealed that the OS 005, OS 263 and OS 157 closely related to Streptomyces djakartensis, Streptomyces olivaceus and Nocardiopsis dassonvillei respectively. These results suggested the widespread distribution of the antioxidant and cytotoxic producing actinobacteria in the Oman Sea sediments, which could be considered as promising candidates for the discovery of microbial bioactive compounds.     

Introducing a new conceptual instantaneous unit hydrograph model based on a hydraulic approach

ABSTRACT

A novel approach is introduced for simulation of instantaneous unit hydrographs (IUHs). The model consists of a series of linear reservoirs that are connected to each other, and is referred to as the inter-connected linear reservoir model (ICLRM). By assuming the flow between two reservoirs is a linear function of the difference between the water levels in the reservoirs, a system of first-order linear differential equations is obtained as the ICLRM governing equation. By solving the equations, the discharge from the last reservoir is considered as an IUH. A small-scale laboratory device was constructed for the simulation of IUHs using the model. By studying four hydrographs extracted from the literature, and simulating them using both the ICLRM and the Nash model, it is concluded that the ICLRM can predict these hydrographs more accurately than the Nash model. Due to the simplicity of the construction and operation of the ICLRM and, more importantly, its visual aspect, the ICLRM may be considered as an effective educational tool for studying IUHs.     

Comparison of artificial neural network and multivariate linear regression methods for estimation of daily soil temperature in an arid region

Soil temperature (T _S) strongly influences a wide range of biotic and abiotic processes. As an alternative to direct measurement, indirect determination of T _S from meteorological parameters has been the focus of attention of environmental researchers. The main purpose of this study was to estimate daily T _S at six depths (5, 10, 20, 30, 50 and 100?cm) by using a multilayer perceptron (MLP) artificial neural network (ANN) model and a multivariate linear regression (MLR) method in an arid region of Iran. Mean daily meteorological parameters including air temperature (T _a), solar radiation (R _S), relative humidity (RH) and precipitation (P) were used as input data to the ANN and MLR models. The model results of the MLR model were compared to those of ANN. The accuracy of the predictions was evaluated by the correlation coefficient (r), the root mean-square error (RMSE) and the mean absolute error (MAE) between the measured and predicted T _S values. The results showed that the ANN method forecasts were superior to the corresponding values obtained by the MLR model. The regression analysis indicated that T _a, RH, R _S and P were reasonably correlated with T _S at various depths, but the most effective parameters influencing T _S at different depths were T _a and RH.