Assessing Metal Content in Halophila stipulacea Seagrass as an Indicator of Metal Pollution in the Northern Gulf of Aqaba,Red Sea

Ocean Science Journal - To assess the utility of the seagrass (Halophila stipulacea) for biomonitoring of metal pollution, seagrass samples were collected from four sites along the Jordanian coast...     

Hourly predictive Levenberg–Marquardt ANN and multi linear regression models for predicting of dew point temperature

In this study, the ability of two models of multi linear regression (MLR) and Levenberg–Marquardt (LM) feed-forward neural network was examined to estimate the hourly dew point temperature. Dew point temperature is the temperature at which water vapor in the air condenses into liquid. This temperature can be useful in estimating meteorological variables such as fog, rain, snow, dew, and evapotranspiration and in investigating agronomical issues as stomatal closure in plants. The availability of hourly records of climatic data (air temperature, relative humidity and pressure) which could be used to predict dew point temperature initiated the practice of modeling. Additionally, the wind vector (wind speed magnitude and direction) and conceptual input of weather condition were employed as other input variables. The three quantitative standard statistical performance evaluation measures, i.e. the root mean squared error, mean absolute error, and absolute logarithmic Nash–Sutcliffe efficiency coefficient $ \left( {\left| {{\text{Log}}({\text{NS}})} \right|} \right) $ were employed to evaluate the performances of the developed models. The results showed that applying wind vector and weather condition as input vectors along with meteorological variables could slightly increase the ANN and MLR predictive accuracy. The results also revealed that LM-NN was superior to MLR model and the best performance was obtained by considering all potential input variables in terms of different evaluation criteria.     

A hybrid method for grade estimation using genetic algorithm and neural networks

In the present paper, a new hybrid method is proposed for grade estimation. In this method, the multilayer perceptron (MLP) network is trained using the combination of the Levenberg–Marquardt (LM) method and genetic algorithm (GA). Having a few samples for grade estimation, it is difficult to get a proper result using some function approximation methods like neural networks or geostatistical methods. The neural network training methods are very sensitive to initial weight values when there are a few samples as a training dataset. The main objective of the proposed method is to resolve this problem. Here, our method finds the optimal initial weights by combining GA and LM method. Having the optimal initial values for weights, the local minima are avoided in the training phase and subsequently the neural network sustainability is trained optimally. Furthermore, the hybrid method is applied for grade estimation of Gol-e-Gohar iron ore in south Iran. The proposed method shows significant improvements compared to both conventional MLP and Kriging method. The efficiency of the proposed method gets more highlighted when the training data set is small.     

An empirical method for design of grouted bolts in rock tunnels based on the Geological Strength Index (GSI)

The procedure presented in this paper has been developed for the design of grouted rock bolts in rock tunnels during preliminary design stage. The proposed approach provides a step-by-step procedure to set up a series of practical guidelines for optimum pattern of rock bolting in a variety of rock mass qualities. For this purpose, a new formula for the estimation of the rock load (support pressure) is recommended. Due to its wide-spread acceptance in the field of rock engineering, the Geological Strength Index (GSI) is adopted in support pressure equation. For poor and very poor rock mass where the GSI < 27, the use of Modified-GSI is, instead, recommended. The supporting action is assumed to be provided by rock bolts carrying a total load defined by the rock load height. The mechanism of bolting is assumed to rely on roof arch forming and suspension principle. Integrated with support pressure function, the bolt density parameter is modified in order to provide an optimized bolt pattern for any shape of tunnel. The modified bolt density can also be used in analysis of a reinforced tunnel in terms of Ground Reaction Curve (GRC) in such a way as to evaluate the reinforced rock mass and the tunnel convergence. By doing so, the effectiveness of the bolting pattern is well evaluated. The proposed approach based on GSI is believed to overcome constrains and limitations of existing empirical bolt design methods based on RMR or Q-system, which are doubtful in poor rock mass usage. The applicability of the proposed method is illustrated by the stability analysis and bolt design of a rail-road tunnel in Turkey.     

Analysis of the Moberg et al. (2005) hemispheric temperature reconstruction

The Moberg et al. (Nature 433(7026):613–617, 2005. doi:10.1038/nature03265; M05) reconstruction of northern hemisphere temperature variations from proxy data has been criticised; the M05 method may artificially inflate low-frequency variance relative to reality. We test this assertion by undertaking several pseudoproxy experiments in three climate model simulations—one control run and two forced simulations that include several time-varying radiative forcings. The pseudoproxy series are designed to have the same variance spectra as the real M05 proxies, primarily to mimic the low-resolution character of several series. A simple composite-plus-scale (CPS) method is also analysed. In the CPS case all input data behave like annually resolved proxies. The spectral domain performance of both M05 and CPS is found to be dependent on the noise type and noise level in pseudoproxies, on the variance spectrum of the climate model simulation, and on the degree of data smoothing. CPS performs better than M05 in most investigated cases with the control run, but leads to deflated low-frequency variance in some cases. With M05, low-frequency variance tend to be inflated for the control run but not for one of the forced runs and only very slightly with the other forced simulation. Hence, the M05 approach does not routinely inflate low-frequency variance. In our experiment, the M05 approach performs better in the spectral domain than CPS when applied to forced climate model simulations. The results underscore the importance of evaluating the variance spectrum of climate reconstructions.     

Early Cretaceous migmatitic mafic granulites from the Sabzevar range (NE Iran): implications for the closure of the Mesozoic peri-Tethyan oceans in central Iran

The ophiolitic mélange of the Sabzevar Range (northern Iran) is a remnant of the Mesozoic oceanic basins on the northern margin of the Neotethys that were consumed during the Arabia–Eurasia convergence history. Occurrence of km-scale, dismembered mafic HP granulitic slices is reported in this study. Granulites record an episode of amphibole-dehydratation melting and felsic (tonalite/throndhjemite) melt segregation at c. 1.1 GPa and 800 °C. In situ U(-Th)–Pb geochronology of zircon and titanite grains hosted in melt segregations points to an Early Cretaceous (Albian) age for the metamorphic climax. Results of this study (i) impose reconsideration of the current palaeotectonic models of the Neothetyan convergent margin during the Early Cretaceous and (ii) argue that punctuated events of subduction of short-lived back-arc oceanic basins accompanied the long-lasting history of the Neotethyan subduction in the region.     

RETRACTED ARTICLE: Study of Factors Affecting the Compressive Strength of Sandy Soil Stabilized with Polymer

Material engineers are continually confronted by depletion of quality construction materials for road and airfield construction. Even if good quality construction materials for road and airfield are available, the haul costs may preclude their use. Stabilization of soils in order to improve strength and durability properties often relies on cement, lime, fly ash, and asphalt emulsion. These materials are inexpensive, relatively easy to apply, and provide benefits to many different soil types. In addition, there are a variety of nontraditional soil stabilization/modification additives available from the commercial sector such as polymer emulsions, acids, lignin derivatives, enzymes, tree resin emulsions, and silicates. These additives may be in liquid or solid state and are often touted to be applicable for most soils. Polymers may be easy to apply in permeable materials such as sand and may achieve good stabilization in relatively shorter periods of time. These polymer materials can be used for stabilizing, soil in road shoulders, slopes, and pads of military and emergency airports. In addition, these types of materials can be used to prevent the movement of the dune sands on the sides of railroads and stabilizing the dust on the surface of access roads. Within the present research, two different polymers of wide range of dosages have been applied. Following results have been achieved: (1) These polymers improve the compressive strength from 0.03 N/mm2 for control sample to 5.2 N/mm2 for improved sample. (2) The optimum curing time of dune sands with different polymers is 7 days. (3) The UC strength of stabilized samples soars with an increase in the temperature, in the first 24 h of the curing process. (4) When the concentration of salt increased from 1 to 10 percent, UC strength of stabilized samples decreased.