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.

Generation and analysis of drought stressed subtracted expressed sequence tags from safflower (Carthamus tinctorius L.)

Drought is the most crucial environmental factor that limits productivity of many crop plants. Exploring novel genes and gene combinations is of primary importance in plant drought tolerance research. Stress tolerant genotypes/species are known to express novel stress responsive genes with unique functional significance. Hence, identification and characterization of stress responsive genes from these tolerant species might be a reliable option to engineer the drought tolerance. Safflower has been found to be a relatively drought tolerant crop and thus, it has been the choice of study to characterize the genes expressed under drought stress. In the present study, we have evaluated differential drought tolerance of two cultivars of safflower namely, A1 and Nira using selective physiological marker traits and we have identified cultivar A1 as relatively drought tolerant. To identify the drought responsive genes, we have constructed a stress subtracted cDNA library from cultivar A1 following subtractive hybridization. Analysis of similar to 1,300 cDNA clones resulted in the identification of 667 unique drought responsive ESTs. Protein homology search revealed that 521 (78 %) out of 667 ESTs showed significant similarity to known sequences in the database and majority of them previously identified as drought stress-related genes and were found to be involved in a variety of cellular functions ranging from stress perception to cellular protection. Remaining 146 (22 %) ESTs were not homologous to known sequences in the database and therefore, they were considered to be unique and novel drought responsive genes of safflower. Since safflower is a stress-adapted oil-seed crop this observation has great relevance. In addition, to validate the differential expression of the identified genes, expression profiles of selected clones were analyzed using dot blot (reverse northern), and northern blot analysis. We showed that these clones were differentially expressed under different abiotic stress conditions. The implications of the analyzed genes in abiotic stress tolerance are discussed in our study.

Relay Selection for Geographical Forwarding in Sleep-Wake Cycling Wireless Sensor Networks

Our work is motivated by geographical forwarding of sporadic alarm packets to a base station in a wireless sensor network (WSN), where the nodes are sleep-wake cycling periodically and asynchronously. We seek to develop local forwarding algorithms that can be tuned so as to tradeoff the end-to-end delay against a total cost, such as the hop count or total energy. Our approach is to solve, at each forwarding node enroute to the sink, the local forwarding problem of minimizing one-hop waiting delay subject to a lower bound constraint on a suitable reward offered by the next-hop relay; the constraint serves to tune the tradeoff. The reward metric used for the local problem is based on the end-to-end total cost objective (for instance, when the total cost is hop count, we choose to use the progress toward sink made by a relay as the reward). The forwarding node, to begin with, is uncertain about the number of relays, their wake-up times, and the reward values, but knows the probability distributions of these quantities. At each relay wake-up instant, when a relay reveals its reward value, the forwarding node's problem is to forward the packet or to wait for further relays to wake-up. In terms of the operations research literature, our work can be considered as a variant of the asset selling problem. We formulate our local forwarding problem as a partially observable Markov decision process (POMDP) and obtain inner and outer bounds for the optimal policy. Motivated by the computational complexity involved in the policies derived out of these bounds, we formulate an alternate simplified model, the optimal policy for which is a simple threshold rule. We provide simulation results to compare the performance of the inner and outer bound policies against the simple policy, and also against the optimal policy when the source knows the exact number of relays. Observing the good performance and the ease of implementation of the simple policy, we apply it to our motivating problem, i.e., local geographical routing of sporadic alarm packets in a large WSN. We compare the end-to-end performance (i.e., average total delay and average total cost) obtained by the simple policy, when used for local geographical forwarding, against that obtained by the globally optimal forwarding algorithm proposed by Kim et al. 1].

Integrating biodiversity and conservation with modern agricultural landscapes

To achieve food security and meet the demands of the ever-growing human populations, farming systems have assumed unsustainable practices to produce more from a finite land area. This has been cause for concern mainly due to the often-irreversible damage done to the otherwise productive agricultural landscapes. Agro-ecology is proclaimed to be deteriorating due to eroding integrity of connected ecological mosaics and vulnerability to climate change. This has contributed to declining species diversity, loss of buffer vegetation, fragmentation of habitats, and loss of natural pollinators or predators, which eventually leads to decline in ecosystem services. Currently, a hierarchy of conservation initiatives is being considered to restore ecological integrity of agricultural landscapes. However, the challenge of identifying a suitable conservation strategy is a daunting task in view of socio-ecological factors that may constrain the choice of available strategies. One way to mitigate this situation and integrate biodiversity with agricultural landscapes is to implement offset mechanisms, which are compensatory and balancing approaches to restore the ecological health and function of an ecosystem. This needs to be tailored to the history of location specific agricultural practices, and the social, ecological and environmental conditions. The offset mechanisms can complement other initiatives through which farmers are insured against landscape-level risks such as droughts, fire and floods. For countries in the developing world with significant biodiversity and extensive agriculture, we should promote a comprehensive model of sustainable agricultural landscapes and ecosystem services, replicable at landscape to regional scales. Arguably, the model can be a potential option to sustain the integrity of biodiversity mosaic in agricultural landscapes.

Renewable Energy via Photocatalysis

The generation of renewable energy through photocatalysis is an attractive option to utilize the abundantly available solar radiation for a sustainable future. Photocatalysis refers to charge-carrier, i.e. electron and hole, mediated reactions occurring on a semiconductor surface in presence of ultraviolet or visible light radiation. Photocatalysis is a well established advanced oxidation technique for the decontamination of toxic organic pollutants to CO2 and H2O. However, the generation of energy in the form of hydrogen, hydrocarbon fuels and electricity via photocatalysis is an upcoming field with great many technical challenges towards practical implementation. This review will describe the fundamental reaction mechanism of (i) photocatalytic water splitting, (ii) photocatalytic H-2 generation in presence of different sacrificial agents, (iii) H-2 and electricity generation in a photofuel cell, (iv) photocatalytic reduction of CO2 to hydrocarbons and useful chemicals, and (v) photocatalytic water-gas shift reaction. A historic and recent perspective of the above conversion techniques, especially with regard to the development of TiO2-based and non-TiO2 materials is provided. The activity of different materials for the above reactions based on quantifiers like reaction rate, quantum yield and incident-photon-to-current efficiency is compared, and key design considerations of the ``best'' photocatalyst or photoelectrode is outlined. An overall assessment of the research area indicates that the presently achieved quantum efficiencies for the above reactions are rather moderate in the visible region, and the goal is to develop a catalyst that absorbs visible radiation, provides good charge-carrier separation, and exhibits high stability for long periods of usage.

Treatment of gray water using anaerobic biofilms created on synthetic and natural fibers

Gray water treatment and reuse is an immediate option to counter the upcoming water shortages in various parts of world, especially urban areas. Anaerobic treatment of gray water in houses is an alternative low cost, low energy and low sludge generating option that can meet this challenge. Typical problems of fluctuating VFA, low pH and sludge washout at low loading rates with gray water feedstock was overcome in two chambered anaerobic biofilm reactors using natural fibers as the biofilm support. The long term performance of using natural fiber based biofilms at moderate and low organic loading rates (OLR) have been examined. Biofilms raised on natural fibers (coir, ridge-gourd) were similar to that of synthetic media (PVC, polyethylene) at lower OLR when operated in pulse fed mode without effluent recirculation and achieved 80-90% COD removal at HRT of 2 d showing a small variability during start-up. Confocal microscopy of the biofilms on natural fibers indicated thinner biofilms, dense cell architecture and low extra cellular polymeric substances (EPS) compared to synthetic supports and this is believed to be key factor in high performance at low OLR and low strength gray water. Natural fibers are thus shown to be an effective biofilm support that withstand fluctuating characteristic of domestic gray water. (C) 2013 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Discharge Plasma Combined With Bauxite Residue for Biodiesel Exhaust Cleaning: A Case Study on NOx Removal

Experiments were conducted at laboratory level to treat the oxides of nitrogen (NOx) present in raw and dry biodiesel exhaust utilizing a combination of electric discharge plasma and bauxite residue, i. e., red mud, an industrial waste byproduct from the aluminum industry. In this paper, the adsorption and a possible catalytic property of bauxite residue are discussed. Nonthermal plasma was generated using dielectric barrier discharges initiated by ac/repetitive pulse energization. The effect of corona electrodes on the plasma generation was qualitatively studied through NOx cleaning. The plasma reactor and adsorbent reactors were connected in cascade while treating the exhaust. The diesel generator, running on biodiesel fuel, was electrically loaded to study the effectiveness of the cascade system in cleaning the exhaust. Interestingly, under the laboratory conditions studied, plasma-bauxite residue combination has shown good synergistic properties and enhanced the NOx removal up to about 90%. With proper scaling up, the suggested cascade system may become an economically feasible option to treat the exhaust in larger installations. The results were discussed emphasizing the role of bauxite residue as an adsorbent and as a room temperature catalyst.

Relay Selection with Channel Probing in Sleep-Wake Cycling Wireless Sensor Networks

In geographical forwarding of packets in a large wireless sensor network (WSN) with sleep-wake cycling nodes, we are interested in the local decision problem faced by a node that has ``custody'' of a packet and has to choose one among a set of next-hop relay nodes to forward the packet toward the sink. Each relay is associated with a ``reward'' that summarizes the benefit of forwarding the packet through that relay. We seek a solution to this local problem, the idea being that such a solution, if adopted by every node, could provide a reasonable heuristic for the end-to-end forwarding problem. Toward this end, we propose a local relay selection problem consisting of a forwarding node and a collection of relay nodes, with the relays waking up sequentially at random times. At each relay wake-up instant, the forwarder can choose to probe a relay to learn its reward value, based on which the forwarder can then decide whether to stop (and forward its packet to the chosen relay) or to continue to wait for further relays to wake up. The forwarder's objective is to select a relay so as to minimize a combination of waiting delay, reward, and probing cost. The local decision problem can be considered as a variant of the asset selling problem studied in the operations research literature. We formulate the local problem as a Markov decision process (MDP) and characterize the solution in terms of stopping sets and probing sets. We provide results illustrating the structure of the stopping sets, namely, the (lower bound) threshold and the stage independence properties. Regarding the probing sets, we make an interesting conjecture that these sets are characterized by upper bounds. Through simulation experiments, we provide valuable insights into the performance of the optimal local forwarding and its use as an end-to-end forwarding heuristic.

Long Term Dynamics in CO2 Allowance Prices and Carbon Capture Investments

In this paper we analyse the behaviour of the EU market for CO2 emission allowances; specifically, we focus on the contracts maturing in the Kyoto Protocol's second period of application (2008 to 2012). We calibrate the underlying parameters for the allowance price in the long run and we also calibrate those from the Spanish wholesale electricity market. This information is then used to assess the option to install a carbon capture and storage (CCS) unit in a coal-fired power plant. We use a two-dimensional binomial lattice where costs and profits are valued and the optimal investment time is determined. In other words, we study the trigger allowance prices above which it is optimal to install the capture unit immediately. We further analyse the impact of several variables on the critical prices, among them allowance price volatility and a hypothetical government subsidy. We conclude that, at current permit prices, from a financial point of view, immediate installation does not seem justified. This need not be the case, though, if carbon market parameters change dramatically and/or a specific policy to promote these units is adopted.

Valuing Flexibility: The case of an Integrated Gasification Combined Cycle Power Plant

In this paper we analyze the valuation of options stemming from the flexibility in an Integrated Gasification Combined Cycle (IGCC) Power Plant. First we use as a base case the opportunity to invest in a Natural Gas Combined Cycle (NGCC) Power Plant, deriving the optimal investment rule as a function of fuel price and the remaining life of the right to invest. Additionally, the analytical solution for a perpetual option is obtained. Second, the valuation of an operating IGCC Power Plant is studied, with switching costs between states and a choice of the best operation mode. The valuation of this plant serves as a base to obtain the value of the option to delay an investment of this type. Finally, we derive the value of an opportunity to invest either in a NGCC or IGCC Power Plant, that is, to choose between an inflexible and a flexible technology, respectively. Numerical computations involve the use of one- and two-dimensional binomial lattices that support a mean-reverting process for the fuel prices. Basic parameter values refer to an actual IGCC power plant currently in operation.

Monte Carlo Valuation of natural gas investments

This paper deals with the valuation of energy assets related to natural gas. In particular, we evaluate a baseload Natural Gas Combined Cycle (NGCC) power plant and an ancillary instalation, namely a Liquefied Natural Gas (LNG) facility, in a realistic setting; specifically, these investments enjoy a long useful life but require some non-negligible time to build. Then we focus on the valuation of several investment options again in a realistic setting. These include the option to invest in the power plant when there is uncertainty concerning the initial outlay, or the option's time to maturity, or the cost of CO2 emission permits, or when there is a chance to double the plant size in the future. Our model comprises three sources of risk. We consider uncertain gas prices with regard to both the current level and the long-run equilibrium level; the current electricity price is also uncertain. They all are assumed to show mean reversion. The two-factor model for natural gas price is calibrated using data from NYMEX NG futures contracts. Also, we calibrate the one-factor model for electricity price using data from the Spanish wholesale electricity market, respectively. Then we use the estimated parameter values alongside actual physical parameters from a case study to value natural gas plants. Finally, the calibrated parameters are also used in a Monte Carlo simulation framework to evaluate several American-type options to invest in these energy assets. We accomplish this by following the least squares MC approach.

Going Multinational under Exchange Rate Uncertainty

Published as an article in: Journal of International Money and Finance, 2010, vol. 29, issue 6, pages 1171-1191.

About the limits of metalanguage: An essay on the modelisation of Latin grammatical lexicography

[EN] Progress in methodology in specific fields is usually very closely linked to the technological progress in other areas of knowledge. This justifies the fact that lexicographical techniques have had to wait for the arrival of the IT era of the last decades of the 20th century in order to be able to create specialised electronic dictionaries which can house and systemise enormous amounts of information which can later be dealt with quickly and efficiently. This study proposes a practical-methodological model which aims to solve the grammatical treatment of adverbs in Ancient Latin. We have suggested a list of 5 types, in a decreasing order from a greater to lesser degree of specialisation; technical (T), semi-technical (S-T), instrumental-valued (I-V), instrumental- descriptive (I-D), instrumental-expository (I-E).

Optimal Investment in Energy Efficiency under Uncertainty

41 p.

Optimal Abandonment of Coal-Fired Stations in the EU

36 p.