Bianchi type-I cosmological models with variable G and Λ-term in general relativity

Einstein’s field equations with variable gravitational and cosmological “constant” are considered in presence of perfect fluid for Bianchi type-I space-time. Consequences of the four cases of the phenomenological decay of Λ have been discussed which are consistent with observations. The physical significance of the cosmological models have also been discussed.      

Plane symmetric inhomogeneous cosmological models with a perfect fluid in General Relativity II

We investigate a class of solutions of Einstein equations for the plane symmetric perfect fluid case. If these solutions have shear, they must necessarily be non-static. Some physical and geometric properties of the models are also discussed.      

Mg VIII DIAGNOSTIC LINE RATIOS IN SKYLAB SOLAR OBSERVATIONS

Recent calculations of Mgviii electron and proton impact excitations rates are used to derive theoretical electron temperature (T _e)- and density (N _e)-sensitive emission line ratios involving transitions in the 315–782 Å wavelength range. Some of these ratios are presented in the form of ratio–ratio diagrams, which should in principle allow both N _e and T _e to be deduced. These results are compared with solar observational data from Skylab, but agreement between theory and observation is very poor, probably due to blending.     

Robertson-Walker viscous fluid model

Robertson-Walker cosmological model with bulk viscosity is investigated with equation of statep=(–1). The cosmological solution of the model is obtained with the help of the special law of variation for Hubble's deceleration parameter. Some physical consequences of the solution is studied pertaining to two extreme cases of the equation of state.     

Spatio-Temporal Assessment of Groundwater Potential Zone in the Drought-Prone Area of Bangladesh Using GIS-Based Bivariate Models

Natural Resources Research - Groundwater is one of the most dynamic and renewable natural resources found in the earth’s crust. A spatio-temporal assessment of groundwater potential zone...     

Consolidation and Drainage Characteristics of Expansive Soil Stabilized with Fly Ash and Dolochar

Expansive soils undergo alternate swelling and shrinkage due to cyclic wetting and drying when left to nature. This property of Expansive soil affects its strength and stiffness characteristics thereby causing damage and distress to structures built on them. Industrial wastes can be added scientifically to these soils in modifying and reducing their swelling and shrinkage behaviour and increasing their strength and stiffness. In this technical article, an attempt has been made to study the compressibility and drainage characteristics of these soils using economic and ecofriendly industrial wastes such as Fly Ash and Dolochar as stabilizers. This paper also focuses on many other improved engineering properties of base soil like liquid limit, plasticity index, differential free swell, compaction and consolidation characteristics of Expansive (BC) soil stabilized with Fly Ash and Dolochar in different proportions. The virgin Expansive soil has been collected from eastern part of India (Odisha) and different percentages of Fly Ash (5, 10, 15, 20, 25 and 30 %) and Dolochar (5, 10, 15, 20, 25 and 30 %) were added to it, to predict the influence of these additives on compaction and consolidation characteristics of Expansive soil. Addition of both Fly Ash and Dolochar were found to decrease the index properties such as liquid limit, plastic limit, plasticity index, swelling index and enhancing the consolidation as well as drainage characteristics of Expansive soil. However, the maximum dry density of soil was found to decrease with addition of Fly Ash and increase with addition of Dolochar.     

Geochemistry and petrogenesis of anorogenic(?) granitoids of west Garo Hills,Meghalaya

The granite in Samingiri — Dilsekgiri area occurs as discordant, isolated pluton within the migmatitic terrain of West Garo Hills district, Meghalaya. The pluton is exposed over 140 sq km (18 km × 8 km). It exhibits structures of solid state and piecemeal stoping effect proximal to the contact and enveloped by a contact metamorphic aureole of albite-epidote-hornfels facies. Modally, it is biotite-monzogranite and biotite-syenogranite with minor biotite, chlorite, epidote and sericite and accessories like zircon, apatite, allanite, pyrite, magnetite and sphene. Geochemically, it is marked by restricted composition (69–76 wt% SiO₂), high alkalies, low Ca, metaluminous to strongly peraluminous (Molar Al₂O₃/CaO+Na₂O+K₂O = 0.95 ? 1.54), high FeO/MgO, high Ga/Al, high contents of Rb, Sr, Ba, Y, Zr and Ce and depleted in Ti and P. The field observation, mineralogical and geochemical aspects indicate the post-tectonic nature of West Garo pluton more like as A-type granite formed by partial melting of lower crustal blocks followed by low to moderate degree of fractional differentiation. Low Ca, alkaline nature and peraluminous character point to A-type nature of West Garo granite significantly different from other granites of Meghalaya Plateau. Rb-Sr age (616±86 Ma) of granite, however, corresponds to widespread Middle to Upper Pan African activity, a thermal event prevailed during Late Proterozoic — Early Palaeozoic (500–800 Ma) period, manifested in the form of several granitic intrusions in the basement gneissic complex and the overlying Proterozoic metasediments of the Shillong Group in Meghalaya Plateau.     

An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia

Flooding is one of the most destructive natural hazards that cause damage to both life and property every year, and therefore the development of flood model to determine inundation area in watersheds is important for decision makers. In recent years, data mining approaches such as artificial neural network (ANN) techniques are being increasingly used for flood modeling. Previously, this ANN method was frequently used for hydrological and flood modeling by taking rainfall as input and runoff data as output, usually without taking into consideration of other flood causative factors. The specific objective of this study is to develop a flood model using various flood causative factors using ANN techniques and geographic information system (GIS) to modeling and simulate flood-prone areas in the southern part of Peninsular Malaysia. The ANN model for this study was developed in MATLAB using seven flood causative factors. Relevant thematic layers (including rainfall, slope, elevation, flow accumulation, soil, land use, and geology) are generated using GIS, remote sensing data, and field surveys. In the context of objective weight assignments, the ANN is used to directly produce water levels and then the flood map is constructed in GIS. To measure the performance of the model, four criteria performances, including a coefficient of determination (R ²), the sum squared error, the mean square error, and the root mean square error are used. The verification results showed satisfactory agreement between the predicted and the real hydrological records. The results of this study could be used to help local and national government plan for the future and develop appropriate (to the local environmental conditions) new infrastructure to protect the lives and property of the people of Johor.     

Relative effect method of landslide susceptibility zonation in weathered granite soil: a case study in Deokjeok-ri Creek,South Korea

The objective of this study was to produce and evaluate a landslide susceptibility map for weathered granite soils in Deokjeok-ri Creek, South Korea. The relative effect (RE) method was used to determine the relationship between landslide causative factors (CFs) and landslide occurrence. To determine the effect of CFs on landslides, data layers of aspect, elevation, slope, internal relief, curvature, distance to drainage, drainage density, stream power index, sediment transport index, topographic wetness index, soil drainage character, soil type, soil depth, forest type, timber age, and geology were analyzed in a geographical information system (GIS) environment. A GIS-based landslide inventory map of 748 landslide locations was prepared using data from previous reports, aerial photographic interpretation, and extensive field work. A RE model was generated from a training set consisting of 673 randomly selected landslides in the inventory map, with the remaining 75 landslides used for validation of the susceptibility map. The results of the analysis were verified using the landslide location data. According to the analysis, the RE model had a success rate of 86.3 % and a predictive accuracy of 88.6 %. The validation results showed satisfactory agreement between the susceptibility map and the existing data on landslide locations. The results of this study can therefore be used to mitigate landslide-induced hazards and to plan land use.