LRS Bianchi Type V bulk viscous fluid string dust cosmological model in general relativity

An LRS Bianchi Type V bulk viscous fluid dust distribution string cosmological model in General Relativity is investigated. It has been shown that if coefficient of bulk viscosity (ζ) is proportional to the expansion (θ) in the model then string cosmological model for Bianchi Type V space-time is possible. In absence of bulk viscosity(ζ) i.e. when ζ → 0 then there is no string cosmological model for Bianchi Type V space-time. The physical and geometrical aspects are also discussed. This revised version was published online in July 2006 with corrections to the Cover Date.     

Active spreading and hydrothermalism in North Fiji Basin (SW Pacific). Results of Japanese French Cruise Kaiyo 87

The aim of the Japanese-French Kaiyo 87 cruise was the study of the spreading axis in the North Fiji Basin (SW Pacific). A Seabeam and geophysical survey allowed us to define the detailed structure of the active NS spreading axis between 16° and 22° S and its relationships with the left lateral motion of the North Fiji Fracture Zone. Between 21° S and 18°10′ S, the spreading axis trends NS. From 18°10 S to 16°40 S the orientation of the spreading axis changes from NS to 015°. North of 16°40′ S the spreading axis trends 160°. These two 015° and 160° branches converge with the left lateral North Fiji fracture zone around 16°40′ S to define an RRFZ triple junction. Water sampling, dredging and photo TV deep towing give new information concerning the hydrothermal activity along the spreading axis. The discovery of hydrothermal deposits associated with living communities confirms this activity.     

A Preliminary Evaluation on the Prospects of Hydrocarbon Potential in the Carbonaceous Shales of Spiti and Chikkim Formations,Tethys Himalaya,India

In the present investigation, an attempt has been made to explore the possibility of hydrocarbon prospects in the carbonaceous shale deposits of Spiti and Chikkim formations exposed in the Spiti valley of the Tethys Himalaya. Twenty samples, collected from successive levels of these litho-units, have been subjected to maceral analysis, Rock-Eval Pyrolysis and six samples to Fourier Transform Infra-red Spectroscopy (FTIR) and nuclear magnetic resonance (NMR) analyses. The study reveals the presence of mainly kerogen-III type of organic matter but some of the shale samples have shown a good amount of total organic carbon (TOC) to the tune of 3.19% which is sufficient to produce hydrocarbon. The results indicate the presence of methane occurring as free and fixed hydrocarbon in the shale samples. Few levels are especially rich in hydrocarbon. They have shown encouraging results with potential for generating liquid as well as lighter hydrocarbon. The data is also supported by the FTIR and NMR studies.     

The age of the Nodular Limestone Formation (Late Cretaceous), Narmada Basin,central India

The age of the marine Nodular Limestone Formation of the Bagh Group is refined at Substage level through ammonoid and inoceramid index taxa. The study is based on the fresh collections from three well-defined successive intervals (Lower Karondia, Upper Karondia and Chirakhan members) of this formation having excellent exposures in different localities of the Narmada Basin, central India. The first record of the widely distributed Turonian ammonoid genera Spathites Kummel and Decker and Collignoniceras Breistroffer from the Nodular Limestone Formation constrained its age exclusively to Turonian. The Early Turonian species Spathites (Jeanrogericeras) aff. revelieranus (Courtiller) and Mytiloides labiatus (Sclotheim) occur in the lower part, while the Middle Turonian marker Collignoniceras cf. carolinum (d’Obrbigny) and Inoceramus hobetsensis (Nagao and Matsumoto) occurs in the upper part of the Karondia Member. The record of the index species Inoceramus teshioensis (Nagao and Matsumoto) in association with Placenticeras mintoi Vredenburg from Chirakhan Member allows a definite Late Turonian age. The present contribution is an attempt to resolve the controversies in the age of the Nodular Limestone Formation and also demarcation of the three divisions (Early, Middle and Late) of the Turonian Stage in the Narmada Basin, central India.     

Lepton loss and entropy generation in stellar collapse

The effects of uncertainties in determining the loss of neutrinos and the generation of entropy during the collapse of a stellar core are studied using a simple spherically-symmetric homologous collapse model with an improved treatment for the excited nuclei. It is found that the neutrino loss and entropy generation are not altogether insensitive to most variations of the assumptions regarding the input physics, collapse rate and initial conditions and in particular the need to determine accurately beta capture rates in stellar collapse is pointed out.     

Variability of mini cold pool off the southern tip of India as revealed from a thermodynamic upper ocean model

A 2.5-layer thermodynamic ocean model has been used to understand the processes associated with the formation of cold pool off southern tip of India. The mean model simulations from the 13 year integration for the period 1992–2004 renders a cold region off southern tip of India during the months of June to September which is recognized as mini cold pool (MCP). The inter-annual and intra-seasonal variability of the MCP for the 5 years from 2000 to 2004 is explored in detail in the present paper. The analysis of model SST shows intense and widespread MCP during the long breaks occurred in the months of July and August of the bad monsoon years 2002 and 2004. The intense cooling is in response to the wind induced upwelling and the resultant entrainment of cold water from the bottom layer. The presence of cyclonic gyre in the model currents also supports the intense MCP which might modulate the monsoon during break phase.     

Uncertainty assessment of the multilayer perceptron (MLP) neural network model with implementation of the novel hybrid MLP-FFA method for prediction of biochemical oxygen demand and dissolved oxygen: a case study of Langat River

Accurate prediction of the chemical constituents in major river systems is a necessary task for water quality management, aquatic life well-being and the overall healthcare planning of river systems. In this study, the capability of a newly proposed hybrid forecasting model based on the firefly algorithm (FFA) as a metaheuristic optimizer, integrated with the multilayer perceptron (MLP-FFA), is investigated for the prediction of monthly water quality in Langat River basin, Malaysia. The predictive ability of the MLP-FFA model is assessed against the MLP-based model. To validate the proposed MLP-FFA model, monthly water quality data over a 10-year duration (2001–2010) for two different hydrological stations (1L04 and 1L05) provided by the Irrigation and Drainage Ministry of Malaysia are used to predict the biochemical oxygen demand (BOD) and dissolved oxygen (DO). The input variables are the chemical oxygen demand (COD), total phosphate (PO₄), total solids, potassium (K), sodium (Na), chloride (Cl), electrical conductivity (EC), pH and ammonia nitrogen (NH₄-N). The proposed hybrid model is then evaluated in accordance with statistical metrics such as the correlation coefficient (r), root-mean-square error, % root-mean-square error and Willmott’s index of agreement. Analysis of the results shows that MLP-FFA outperforms the equivalent MLP model. Also, in this research, the uncertainty of a MLP neural network model is analyzed in relation to the predictive ability of the MLP model. To assess the uncertainties within the MLP model, the percentage of observed data bracketed by 95 percent predicted uncertainties (95PPU) and the band width of 95 percent confidence intervals (d-factors) are selected. The effect of input variables on BOD and DO prediction is also investigated through sensitivity analysis. The obtained values bracketed by 95PPU show about 77.7%, 72.2% of data for BOD and 72.2%, 91.6% of data for DO related to the 1L04 and 1L05 stations, respectively. The d-factors have a value of 1.648, 2.269 for BOD and 1.892, 3.480 for DO related to the 1L04 and 1L05 stations, respectively. Based on the values in both stations for the 95PPU and d-factor, it is concluded that the neural network model has an acceptably low degree of uncertainty applied for BOD and DO simulations. The findings of this study can have important implications for error assessment in artificial intelligence-based predictive models applied for water resources management and the assessment of the overall health in major river systems.     

Tropical cyclone contribution to extreme rainfall over southwest Pacific Island nations

Southwest Pacific nations are among some of the worst impacted and most vulnerable globally in terms of tropical cyclone (TC)-induced flooding and accompanying risks. This study objectively quantifies the fractional contribution of TCs to extreme rainfall (hereafter, TC contributions) in the context of climate variability and change. We show that TC contributions to extreme rainfall are substantially enhanced during active phases of the Madden–Julian Oscillation and by El Niño conditions (particularly over the eastern southwest Pacific region); this enhancement is primarily attributed to increased TC activity during these event periods. There are also indications of increasing intensities of TC-induced extreme rainfall events over the past few decades. A key part of this work involves development of sophisticated Bayesian regression models for individual island nations in order to better understand the synergistic relationships between TC-induced extreme rainfall and combinations of various climatic drivers that modulate the relationship. Such models are found to be very useful for not only assessing probabilities of TC- and non-TC induced extreme rainfall events but also evaluating probabilities of extreme rainfall for cases with different underlying climatic conditions. For example, TC-induced extreme rainfall probability over Samoa can vary from ~ 95 to ~ 75% during a La Niña period, if it coincides with an active or inactive phase of the MJO, and can be reduced to ~ 30% during a combination of El Niño period and inactive phase of the MJO. Several other such cases have been assessed for different island nations, providing information that have potentially important implications for planning and preparing for TC risks in vulnerable Pacific Island nations.

     

Directional spread parameter at intermediate water depth

The characteristics of directional spread parameters at intermediate water depth are investigated based on a cosine power ‘2s' directional spreading model. This is based on wave measurements carried out using a Datawell directional waverider buoy in 23 m water depth. An empirical equation for the frequency dependent directional spreading parameter is presented. Directional spreading function estimated based on the Maximum Entropy Method is compared with those obtained using a cosine power ‘2s' parameter model. A set of empirical equations relating the directional spreading parameter corresponding to the peak of wave spectrum to other wave parameters like significant wave height and period are obtained. It shows that the wave directional spreading at peak wave frequency can be related to the non-linearity parameter, which allows estimation of directional spreading without reference to wind information.