Magellanic Stream: A possible tool for studying dark halo model

We model the dynamics of Magellanic Stream with the ram-pressure scenario in the logarithmic and power-law galactic halo models and construct numerically the past orbital history of Magellanic Clouds and Magellanic Stream. The parameters of models include the asymptotic rotation velocity of spiral arms, halo flattening, core radius and rising or falling parameter of rotation curve. We obtain the best-fit parameters of galactic models through the maximum likelihood analysis, comparing the high resolution radial velocity data of HI in Magellanic Stream with that of theoretical models. The initial condition of the Magellanic Clouds is taken from the six different values reported in the literature. We find that oblate and nearly spherical shape halos provide a better fit to the observation than the prolate halos. This conclusion is almost independent of choosing the initial conditions and is valid for both logarithmic and power-law models.     

Palaeoecology and biostratigraphy of early Cretaceous (Aptian) calcareous nannofossils and the δCcarb isotope record from NE Iran

Upper Barremian-Lower Aptian sediments of the Sarcheshmeh and Sanganeh formations in the Kopet Dagh area, northeast Iran were studied with regard to their calcareous nannofossil content and their δ¹³C_carb signal. The sediments are composed mainly of marlstones, argillaceous limestones and limestones. Based on the occurrence of biostratigraphic index taxa, the calcareous nannofossil zones NC5, NC6 and the NC7A Subzone were recognised. The calcareous nannofossils and the δ¹³C_carb data enable recognition of the early Aptian Oceanic Anoxic Event 1a (OAE 1a). The deposits of the OAE 1a interval are characterised by the rarity of nannoconids and a sharp negative δ¹³C_carb excursion (1.36‰), followed by an abrupt positive δ¹³C_carb excursion of 4-5‰; both events have been recognised elsewhere in OAE 1a deposits in the Tethys. In the OAE 1a interval, the relative abundance of Watznaueria barnesiae/Watznaueria fossacincta is higher (more than 40%) than that of Biscutum spp., Discorhabdus spp. and Zeugrhabdotus spp., which indicates dissolution. In the upper part of the section, the higher relative abundance of mesotrophic and oligotrophic taxa (Watznaueria spp. and nannoconids respectively) and the enhanced relative abundance of eutrophic taxa (Biscutum spp., Discorhabdus spp., Zeugrhabdotus spp.) is indicative of an environment with slightly increased nutrient content. The presence of warm water taxa (Rhagodiscus asper and nannoconids) and the absence of cool water taxa (Repagulum and Crucibiscutum) suggest warm surface-water conditions.     

Mineral Potential Mapping Via TOPSIS with Hybrid AHP–Shannon Entropy Weighting of Evidence: A Case Study for Porphyry-Cu,Farmahin Area,Markazi Province,Iran

This paper presents an AHP–Shannon Entropy weighting approach as a new hybrid method for assigning evidential weights in mineral potential mapping. For demonstrating the proposed method, a case study was selected for porphyry-Cu potential mapping in Markazi Province, Iran. Then, geo-datasets were gathered, and evidence layers were generated for integration by TOPSIS method (via combination of AHP–Shannon Entropy weighting). Finally, the output mineral potential map was evaluated by field checking and chemical analysis of samples. Two outcrops with evidence of a porphyry system were encountered in areas with high potential values. In addition, there was good correlation between high potential values and Cu content of samples taken from the field. Hence, the usefulness of the AHP–Shannon Entropy weighting of evidence for MPM was demonstrated.     

Probabilistic residual capacity assessment of mainshock-damaged multi-span simply supported concrete girder bridges subjected to aftershocks

Bulletin of Earthquake Engineering - Since post-mainshock events following a major earthquake are likely to occur, it is imperative to have an understanding of the functionality status of...     

Prediction of longitudinal dispersion coefficient in natural rivers using a cluster-based Bayesian network

The longitudinal dispersion coefficient is a key element in determining the distribution and transmission of pollution, especially when cross-sectional mixing is completed. However, the existing predictive techniques for this purpose exhibit great amounts of uncertainty. The main objective of this study is to present a more accurate model for predicting longitudinal dispersion coefficient in natural rivers and streams. Bayesian network (BN) approach was considered in the modeling procedure. Two forms of input variables including dimensional and dimensionless parameters were examined to find the best model structure. In order to increase the performance of the model, the clustering method as a preprocessing data technique was applied to categorize the data in separate groups with similar characteristics. An expansive data set consisting of 149 field measurements was used for training and testing steps of the developed models. Three performance evaluation criteria were adopted for comparison of the results of the different models. Comparison of the present results with the artificial neural network (ANN) model and also well-known existing equations showed the efficiency of the present model. The performance of dimensionless BN model 30% is more than dimensional ones in terms of the root mean square error. The accuracy criterion was increased from 70 to 83% by performing clustering analysis on the BN model. The BN-cluster model 43% is more accurate than ANN model in terms of the accuracy criterion. The results indicate that the BN-cluster model give 16% better results than the best available considered model in terms of the accuracy criterion. The developed model provides a suitable approach for predicting pollutant transport in natural rivers.     

Geochemistry of Carboniferous Sandstones (Sardar Formation), East‐Central Iran: Implication for Provenance and Tectonic Setting

Geochemical analysis of sandstones from the Sardar Formation (from two stratigraphic successions) in east-central Iran were used for identification of geochemical characterization of sandstones, provenance and tectonic setting. Sandstones in the two lithostratigraphic successions have similar chemical compositions suggesting a common provenance. Bulk-rock geochemistry analysis of Carboniferous sandstones from Sardar Formation indicates that they are mainly quartz dominated and are classified as quartzarenites, sublitharenites and subarkoses, derived from acid igneous to intermediate igneous rocks. Discrimination function analysis indicates that the sandstones of Sardar Formation were derived from quartzose sedimentary provenance in a recycled orogenic setting. Also, major and trace elements in sandstones of Sardar Formation (e.g., K2O/Na2O vs. SiO2) indicate deposition in a stable passive continental margin (PM). Chemical index of alteration (CIA) for these rocks (> 65%) suggests a moderate to relatively high degree of weathering in the source area.     

Biostratigraphy of the Surgah formation in Kuh-e-Surgah and correlation with Tang-e-Gerab (West of Iran)

In biostratigraphic studies of the Surgah formation in the Kuh-e-Surgah section, 145 samples were collected. The thickness of the Surgah formation is about 175 m, and it consists mainly of limestone and shale. The lower and upper boundaries of the Surgah formation are Sarvak and Ilam formations, respectively, and they are conformable with sharp lithology. Seventeen species which belong to six genera of planktonic foraminifera and four biozones have been identified in this study. Based on foraminifera assemblages and biozone determinations, the age of the Surgah formation is Late Turonian to Early Late Santonian. This section is correlated with the Tang-e-Gerab section.