A Single-Crystal Study Of The Defect Chemistry And Transport-Properties Of Silver Selenide, Ag2+Delta-Se

Electronic and ionic conductivities of silver selenide crystal (Ag$_2+\delta$ Se) have been measured over a range of stoichiometry through the $\alpha - \beta$ transition by using solid state electrochemical techniques. In the high temperature $\beta$-phase Ag$_2$Se shows metallic behaviour of electronic conductivity for high values of $\delta$; with decrease in $\delta$, the conductivity of the material exhibits a transition. The magnitude of change in electronic conductivity at the $\alpha - \beta$ transition is also determined by stoichiometry. Ionic conductivity of the $\beta$-phase does not vary significantly with stochiometry. Ionic conductivity of the $\beta$-does not vary significantly with stoichiometry. A model to explain the observed transport properties has been suggested.

The diatom genus Gomphonema Ehrenberg in India: Checklist and description of three new species

We have compiled a checklist of Gomphonema Ehrenberg taxa reported previously from India. From forty-nine references, over 100 Gomphonema taxa have been reported, including 39 new taxon descriptions. In addition to these previous reports of Gomphonema taxa, we describe three new species. G. gandhii Karthick & Kociolek, sp. nov., G. difformum Karthick & Kociolek, sp. nov. and G. diminutum Karthick & Kociolek, sp. nov., all from hill streams of Western Ghats, India. Frustule morphology, as studied in light and scanning electron microscopy, is compared with that of other recently described Gomphonema species from Africa and Asia. All three Indian species have distinctly dilated proximal raphe ends, in addition to differentiated apical pore fields, septa, pseudosepta and a round external stigma! opening. Gomphonema gandhii is linear-lanceolate-clavate, has a wide axial area, and is 19-51 mu m long, 3-7 mu m broad. Gomphonema difformum is smaller than G. gandhii, and has a hyaline area around the headpole. Gomphonema diminuta is much smaller and narrower than the other two species. These species are distinct from their closest congeners by their sizes, shape and structure of the head pole, and striae densities. All these species were described from low nutrient, neutral, low ionic content streams of Western Ghats. As most other species described from tropical region these three species appear to be endemic to India. Moreover, within India they have hitherto only been found in Western Ghats, one of the twelve biodiversity hotspots of the World.

Synthesis of new (Bi, La)(3)MSb(2)O(11) phases (M = Cr, Mn, Fe) with KSbO(3)-type structure and their magnetic and photocatalytic properties

Synthesis and structure of new (Bi, La)(3)MSb(2)O(11) phases (M = Cr, Mn, Fe) are reported in conjunction with their magnetic and photocatalytic properties. XRD refinements reflect that Bi(3)CrSb(2)O(11), Bi(2)LaCrSb(2)O(11), Bi(2)LaMnSb(2)O(11) and Bi(2)LaFeSb(2)O(11) adopt KSbO(3)-type structure (space group, Pn (3) over bar). The structure can be described through three interpenetrating networks where the first is the (M/Sb)O(6) octahedral network and other two are the identical networks having Bi(6)O(4) composition. The magnetic measurements on Bi(2)LaCrSb(2)O(11) and Bi(2)LaMnSb(2)O(11) show paramagnetic behaviour with magnetic moments close to the expected spin only magnetic moments of Cr(+3) and Mn(+3). The UV-Visible diffuse reflectance spectra are broad and indicate that these materials possess a bandgap of similar to 2 eV. The photocatalytic activity of these materials has been investigated by degrading Malachite Green (MG) under exposure to UV light.

Pt-Au/C cathode with enhanced oxygen-reduction activity in PEFCs

Carbon-supported Pt-Au (Pt-Au/C) catalyst is prepared separately by impregnation, colloidal and micro-emulsion methods, and characterized by physical and electrochemical methods. Highest catalytic activity towards oxygen-reduction reaction (ORR) is exhibited by Pt-Au/C catalyst prepared by colloidal method. The optimum atomic ratio of Pt to Au in Pt-Au/C catalyst prepared by colloidal method is determined using linear-sweep and cyclic voltammetry in conjunction with cell-polarization studies. Among 3:1, 2:1 and 1:1 Pt-Au/C catalysts, (3:1) Pt-Au/C exhibits maximum electrochemical activity towards ORR. Powder X-ray diffraction pattern and transmission electron micrograph suggest Pt-Au alloy nanoparticles to be well dispersed onto the carbon-support. Energy dispersive X-ray analysis and inductively coupled plasma-optical emission spectroscopy data suggest that the atomic ratios of the alloying elements match well with the expected values. A polymer electrolyte fuel cell (PEFC) operating at 0 center dot 6 V with (3:1) Pt-Au/C cathode delivers a maximum power-density of 0 center dot 65 W/cm (2) in relation to 0 center dot 53 W/cm (2) delivered by the PEFC with pristine carbon-supported Pt cathode.

Landslide susceptibility mapping in the downstream region of Sharavathi river basin, Central Western Ghats

Landslides are hazards encountered during monsoon in undulating terrains of Western Ghats causing geomorphic make over of earth surface resulting in significant damages to life and property. An attempt is made in this paper to identify landslides susceptibility regions in the Sharavathi river basin downstream using frequency ratio method based on the field investigations during July- November 2007. In this regard, base layers of spatial data such as topography, land cover, geology and soil were considered. This is supplemented with the field investigations of landslides. Factors that influence landslide were extracted from the spatial database. The probabilistic model -frequency ratio is computed based on these factors. Landslide susceptibility indices were computed and grouped into five classes. Validation of LHS, showed an accuracy of 89% as 25 of the 28 regions tallied with the field condition of highly vulnerable landslide regions. The landslide susceptible map generated for the downstream would be useful for the district officials to implement appropriate mitigation measures to reduce hazards.

Soft classification based Sub-pixel allocation model

Land cover (LC) refers to what is actually present on the ground and provide insights into the underlying solution for improving the conditions of many issues, from water pollution to sustainable economic development. One of the greatest challenges of modeling LC changes using remotely sensed (RS) data is of scale-resolution mismatch: that the spatial resolution of detail is less than what is required, and that this sub-pixel level heterogeneity is important but not readily knowable. However, many pixels consist of a mixture of multiple classes. The solution to mixed pixel problem typically centers on soft classification techniques that are used to estimate the proportion of a certain class within each pixel. However, the spatial distribution of these class components within the pixel remains unknown. This study investigates Orthogonal Subspace Projection - an unmixing technique and uses pixel-swapping algorithm for predicting the spatial distribution of LC at sub-pixel resolution. Both the algorithms are applied on many simulated and actual satellite images for validation. The accuracy on the simulated images is ~100%, while IRS LISS-III and MODIS data show accuracy of 76.6% and 73.02% respectively. This demonstrates the relevance of these techniques for applications such as urban-nonurban, forest-nonforest classification studies etc.

Infrared studies of the phase transitions of alkylammonium halides, RNH3X, and bis-(alkylammonium) tetrahalogenometallates(II), (RNH3)2MX4, (R = alkyl, M = metal, X = Cl or Br)

Internal vibration modes of bis-(alkylammonium) tetrachlorometallates(II) and the corresponding alkylammonium chlorides have been studied through their phase transitions using infrared spectroscopy. The studies show that the vibrational states of alkylammonium ions change markedly through the phase transitions. Spectra of the analogous tetrabromometallates and alkylammonium bromides also confirm this behaviour. There is appreciable motion of the alkylammonium ions in the high-temperature phases; thus, CH3NH+3 ions are essentially undistorted in these phases. The low-temperature, ordered phases show evidence of stronger hydrogen bonding of the cations and for the presence of C—N torsional modes.

Image fusion in GRDSS for Land use Mapping

Image fusion techniques are useful to integrate the geometric detail of a high-resolution panchromatic (PAN) image and the spectral information of a low-resolution multispectral (MSS) image, particularly important for understanding land use dynamics at larger scale (1:25000 or lower), which is required by the decision makers to adopt holistic approaches for regional planning. Fused images can extract features from source images and provide more information than one scene of MSS image. High spectral resolution aids in identification of objects more distinctly while high spatial resolution allows locating the objects more clearly. The geoinformatics technologies with an ability to provide high-spatial-spectral-resolution data helps in inventorying, mapping, monitoring and sustainable management of natural resources. Fusion module in GRDSS, taking into consideration the limitations in spatial resolution of MSS data and spectral resolution of PAN data, provide high-spatial-spectral-resolution remote sensing images required for land use mapping on regional scale. GRDSS is a freeware GIS Graphic User Interface (GUI) developed in Tcl/Tk is based on command line arguments of GRASS (Geographic Resources Analysis Support System) with the functionalities for raster analysis, vector analysis, site analysis, image processing, modeling and graphics visualization. It has the capabilities to capture, store, process, analyse, prioritize and display spatial and temporal data.

Solar energy decision support system

Energy plays a prominent role in human society. As a result of technological and industrial development,the demand for energy is rapidly increasing. Existing power sources that are mainly fossil fuel based are leaving an unacceptable legacy of waste and pollution apart from diminishing stock of fuels.Hence, the focus is now shifted to large-scale propagation of renewable energy. Renewable energy technologies are clean sources of energy that have a much lower environmental impact than conventional energy technologies. Solar energy is one such renewable energy. Most renewable energy comes either directly or indirectly from the sun. Estimation of solar energy potential of a region requires detailed solar radiation climatology, and it is necessary to collect extensive radiation data of high accuracy covering all climatic zones of the region. In this regard, a decision support system (DSS)would help in estimating solar energy potential considering the region’s energy requirement.This article explains the design and implementation of DSS for assessment of solar energy. The DSS with executive information systems and reporting tools helps to tap vast data resources and deliver information. The main hypothesis is that this tool can be used to form a core of practical methodology that will result in more resilient in time and can be used by decision-making bodies to assess various scenarios. It also offers means of entering, accessing, and interpreting the information for the purpose of sound decision making.

Geographic Resources Decision Support System – an Open Source GIS

Fully structured and matured open source spatial and temporal analysis technology seems to be the official carrier of the future for planning of the natural resources especially in the developing nations. This technology has gained enormous momentum because of technical superiority, affordability and ability to join expertise from all sections of the society. Sustainable development of a region depends on the integrated planning approaches adopted in decision making which requires timely and accurate spatial data. With the increased developmental programmes, the need for appropriate decision support system has increased in order to analyse and visualise the decisions associated with spatial and temporal aspects of natural resources. In this regard Geographic Information System (GIS) along with remote sensing data support the applications that involve spatial and temporal analysis on digital thematic maps and the remotely sensed images. Open source GIS would help in wide scale applications involving decisions at various hierarchical levels (for example from village panchayat to planning commission) on economic viability, social acceptance apart from technical feasibility. GRASS (Geographic Resources Analysis Support System, http://wgbis.ces.iisc.ernet.in/grass) is an open source GIS that works on Linux platform (freeware), but most of the applications are in command line argument, necessitating a user friendly and cost effective graphical user interface (GUI). Keeping these aspects in mind, Geographic Resources Decision Support System (GRDSS) has been developed with functionality such as raster, topological vector, image processing, statistical analysis, geographical analysis, graphics production, etc. This operates through a GUI developed in Tcltk (Tool command language / Tool kit) under Linux as well as with a shell in X-Windows. GRDSS include options such as Import /Export of different data formats, Display, Digital Image processing, Map editing, Raster Analysis, Vector Analysis, Point Analysis, Spatial Query, which are required for regional planning such as watershed Analysis, Landscape Analysis etc. This is customised to Indian context with an option to extract individual band from the IRS (Indian Remote Sensing Satellites) data, which is in BIL (Band Interleaved by Lines) format. The integration of PostgreSQL (a freeware) in GRDSS aids as an efficient database management system.

WEPA: Wind energy potential assessment-spatial decision support system

Spatial Decision Support System (SDSS) assist in strategic decision-making activities considering spatial and temporal variables, which help in Regional planning. WEPA is a SDSS designed for assessment of wind potential spatially. A wind energy system transforms the kinetic energy of the wind into mechanical or electrical energy that can be harnessed for practical use. Wind energy can diversify the economies of rural communities, adding to the tax base and providing new types of income. Wind turbines can add a new source of property value in rural areas that have a hard time attracting new industry. Wind speed is extremely important parameter for assessing the amount of energy a wind turbine can convert to electricity: The energy content of the wind varies with the cube (the third power) of the average wind speed. Estimation of the wind power potential for a site is the most important requirement for selecting a site for the installation of a wind electric generator and evaluating projects in economic terms. It is based on data of the wind frequency distribution at the site, which are collected from a meteorological mast consisting of wind anemometer and a wind vane and spatial parameters (like area available for setting up wind farm, landscape, etc.). The wind resource is governed by the climatology of the region concerned and has large variability with reference to space (spatial expanse) and time (season) at any fixed location. Hence the need to conduct wind resource surveys and spatial analysis constitute vital components in programs for exploiting wind energy. SDSS for assessing wind potential of a region / location is designed with user friendly GUI’s (Graphic User Interface) using VB as front end with MS Access database (backend). Validation and pilot testing of WEPA SDSS has been done with the data collected for 45 locations in Karnataka based on primary data at selected locations and data collected from the meteorological observatories of the India Meteorological Department (IMD). Wind energy and its characteristics have been analysed for these locations to generate user-friendly reports and spatial maps. Energy Pattern Factor (EPF) and Power Densities are computed for sites with hourly wind data. With the knowledge of EPF and mean wind speed, mean power density is computed for the locations with only monthly data. Wind energy conversion systems would be most effective in these locations during May to August. The analyses show that coastal and dry arid zones in Karnataka have good wind potential, which if exploited would help local industries, coconut and areca plantations, and agriculture. Pre-monsoon availability of wind energy would help in irrigating these orchards, making wind energy a desirable alternative.

Comparative Assessment of Techniques for Bioresource Monitoring Using GIS and Remote Sensing

Growing concern over the status of global and regional bioenergy resources has necessitated the analysis and monitoring of land cover and land use parameters on spatial and temporal scales. The knowledge of land cover and land use is very important in understanding natural resources utilization, conversion and management. Land cover, land use intensity and land use diversity are land quality indicators for sustainable land management. Optimal management of resources aids in maintaining the ecosystem balance and thereby ensures the sustainable development of a region. Thus sustainable development of a region requires a synoptic ecosystem approach in the management of natural resources that relates to the dynamics of natural variability and the effects of human intervention on key indicators of biodiversity and productivity. Spatial and temporal tools such as remote sensing (RS), geographic information system (GIS) and global positioning system (GPS) provide spatial and attribute data at regular intervals with functionalities of a decision support system aid in visualisation, querying, analysis, etc., which would aid in sustainable management of natural resources. Remote sensing data and GIS technologies play an important role in spatially evaluating bioresource availability and demand. This paper explores various land cover and land use techniques that could be used for bioresources monitoring considering the spatial data of Kolar district, Karnataka state, India. Slope and distance based vegetation indices are computed for qualitative and quantitative assessment of land cover using remote spectral measurements. Differentscale mapping of land use pattern in Kolar district is done using supervised classification approaches. Slope based vegetation indices show area under vegetation range from 47.65 % to 49.05% while distance based vegetation indices shoes its range from 40.40% to 47.41%. Land use analyses using maximum likelihood classifier indicate that 46.69% is agricultural land, 42.33% is wasteland (barren land), 4.62% is built up, 3.07% of plantation, 2.77% natural forest and 0.53% water bodies. The comparative analysis of various classifiers, indicate that the Gaussian maximum likelihood classifier has least errors. The computation of talukwise bioresource status shows that Chikballapur Taluk has better availability of resources compared to other taluks in the district.

Bioenergy Status of Sharavathi River Basin, Western Ghats, India

Most of the developing countries including India depend heavily on bioenergy and it accounts for about 15% of the global energy usage. Its role in meeting a region’s requirement has increased the interest of assessing the status of biomass availability in a region. The present work deals with the bioenergy status in the Linganamakki reservoir catchment of the Sharavathi river basin, Western Ghats,India, by assessing the energy supply and sector wise energy consumption. The study reveals that majority of the households (92.17%) depend on fuelwood for their domestic energy needs with the per capita fuelwood consumption of 1.2 tonnes/year, which is higher than the national average (0.7 tonnes/year). This higher dependence on fuelwood has contributed to the degradation of forests,resulting in scarcity of bioresources necessitating exploration of viable energy alternatives to meet the growing energy demand.