34 resultados para Market analysis strategy


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A thermal model for a conventional biogas plant has been developed in order to understand the heat transfer from the slurry and the gas holder to the surrounding earth and air respectively. The computations have been performed for two conditions : (i) when the slurry is at an ambient temperature of 20°C, and (ii) when it is at 35°C, the optimum temperature for anaerobic fermentation. Under both these conditions, the gas holder is the major “culprit” with regard to heat losses from the biogas plant. The calculations provide an estimate for the heat which has to be supplied by external means to compensate for the net heat losses which occur if the slurry is to be maintained at 35°C. Even if this external supply of heat is realised through (the calorific value of) biogas, there is a net increase in the biogas output, and therefore a net benefit, by operating the plant at 35°C. At this elevated temperature, the cooling effect of adding the influent at ambient temperature is not insignificant. In conclusion, the results of the thermal analysis are used to define a strategy for operating biogas plants at optimum temperatures, or at higher temperatures than the ambient.

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One of the most important factors that affect the pointing of precision payloads and devices in space platforms is the vibration generated due to static and dynamic unbalanced forces of rotary equipments placed in the neighborhood of payload. Generally, such disturbances are of low amplitude, less than 1 kHz, and are termed as ‘micro-vibrations’. Due to low damping in the space structure, these vibrations have long decay time and they degrade the performance of payload. This paper addresses the design, modeling and analysis of a low frequency space frame platform for passive and active attenuation of micro-vibrations. This flexible platform has been designed to act as a mount for devices like reaction wheels, and consists of four folded continuous beams arranged in three dimensions. Frequency and response analysis have been carried out by varying the number of folds, and thickness of vertical beam. Results show that lower frequencies can be achieved by increasing the number of folds and by decreasing the thickness of the blade. In addition, active vibration control is studied by incorporating piezoelectric actuators and sensors in the dynamic model. It is shown using simulation that a control strategy using optimal control is effective for vibration suppression under a wide variety of loading conditions.

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Modal approach is widely used for the analysis of dynamics of flexible structures. However, space analysts yet lack an intimate modal analysis of current spacecraft which are rich with flexibility and possess both structural and discrete damping. Mathematical modeling of such spacecraft incapacitates the existing real transformation procedure, for it cannot include discrete damping, demands uncomputable inversion of a modal matrix inaccessible due to its overwhelming size and does not permit truncation. On the other hand, complex transformation techniques entail more computational time and cannot handle structural damping. This paper presents a real transformation strategy which averts inversion of the associated real transformation matrix, allows truncation and accommodates both forms of damping simultaneously. This is accomplished by establishing a key relation between the real transformation matrix and its adjoint. The relation permits truncation of the matrices and leads to uncoupled pairs of coupled first order equations which contain a number of adjoint eigenvectors. Finally these pairs are solved to obtain a literal modal response of forced gyroscopic damped flexibile systems at arbitrary initial conditions.

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We examine the potential for adaptation to climate change in Indian forests, and derive the macroeconomic implications of forest impacts and adaptation in India. The study is conducted by integrating results from the dynamic global vegetation model IBIS and the computable general equilibrium model GRACE-IN, which estimates macroeconomic implications for six zones of India. By comparing a reference scenario without climate change with a climate impact scenario based on the IPCC A2-scenario, we find major variations in the pattern of change across zones. Biomass stock increases in all zones but the Central zone. The increase in biomass growth is smaller, and declines in one more zone, South zone, despite higher stock. In the four zones with increases in biomass growth, harvest increases by only approximately 1/3 of the change in biomass growth. This is due to two market effects of increased biomass growth. One is that an increase in biomass growth encourages more harvest given other things being equal. The other is that more harvest leads to higher supply of timber, which lowers market prices. As a result, also the rent on forested land decreases. The lower prices and rent discourage more harvest even though they may induce higher demand, which increases the pressure on harvest. In a less perfect world than the model describes these two effects may contribute to an increase in the risk of deforestation because of higher biomass growth. Furthermore, higher harvest demands more labor and capital input in the forestry sector. Given total supply of labor and capital, this increases the cost of production in all the other sectors, although very little indeed. Forestry dependent communities with declining biomass growth may, however, experience local unemployment as a result.

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We address risk minimizing option pricing in a regime switching market where the floating interest rate depends on a finite state Markov process. The growth rate and the volatility of the stock also depend on the Markov process. Using the minimal martingale measure, we show that the locally risk minimizing prices for certain exotic options satisfy a system of Black-Scholes partial differential equations with appropriate boundary conditions. We find the corresponding hedging strategies and the residual risk. We develop suitable numerical methods to compute option prices.

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Triplex forming oligonucleotides (TFOs) have the potential to modulate gene expression. While most of the experiments are directed towards triplex mediated inhibition of gene expression the strategy potentially could be used for gene specific activation. In an attempt to design a strategy for gene specific activation in vivo applicable to a large number of genes we have designed a TFO based activator-target system which may be utilized in Saccharomyces cerevisiae or any other system where Gal4 protein is ectopically expressed. The total genome sequence of Saccharomyces cerevisiae and expression profiles were used to select the target genes with upstream poly (pu/py) sequences. We have utilized the paradigm of Gal4 protein and its binding site. We describe here the selection of target genes and design of hairpin-TFO including the targeting sequences containing polypurine stretch found in the upstream promoter regions of weakly expressed genes. We demonstrate, the formation of hairpin-TFO, its binding to Gal4 protein, its ability to form triplex with the target duplex in vitro, the effect of polyethylenimine on complex formation and discuss the implication on in vivo transcription activation.

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Wireless LAN (WLAN) market consists of IEEE 802.11 MAC standard conformant devices (e.g., access points (APs), client adapters) from multiple vendors. Certain third party certifications such as those specified by the Wi-Fi alliance have been widely used by vendors to ensure basic conformance to the 802.11 standard, thus leading to the expectation that the available devices exhibit identical MAC level behavior. In this paper, however, we present what we believe to be the first ever set of experimental results that highlight the fact that WLAN devices from different vendors in the market can have heterogeneous MAC level behavior. Specifically, we demonstrate with examples and data that in certain cases, devices may not be conformant with the 802.11 standard while in other cases, they may differ in significant details that are not a part of mandatory specifications of the standard. We argue that heterogeneous MAC implementations can adversely impact WLAN operations leading to unfair bandwidth allocation, potential break-down of related MAC functionality and difficulties in provisioning the capacity of a WLAN. However, on the positive side, MAC level heterogeneity can be useful in applications such as vendor/model level device fingerprinting.

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The approach taken in this paper in order to modify the scattering features of electrons and phonons and improve the figure of merit (ZT) of thermoelectric PbTe is to alter the microstructure at constant chemistry. A lamellar pattern of PbTe/GeTe at the nano- and microscale was produced in Pb(0.36)Ge(0.64)Te alloy by the diffusional decomposition of a supersaturated solid solution. The mechanism of nanostructuration is most likely a discontinuous spinodal decomposition. A simple model relating the interface velocity to the observed lamellar spacing is proposed. The effects of nanostructuration in Pb(0.36)Ge(0.64)Te alloy on the electrical and thermal conductivity, thermopower and ZT were investigated. It was shown that nanostructuration through the formation of a lamellar pattern of PbTe/GeTe is unlikely to provide a significant improvement due to the occurrence of discontinuous coarsening. However, the present study allows an analysis of possible strategies to improve thermoelectric materials via optimal design of the microstructure and optimized heat treatment. (C) 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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1. Dispersal ability of a species is a key ecological characteristic, affecting a range of processes from adaptation, community dynamics and genetic structure, to distribution and range size. It is determined by both intrinsic species traits and extrinsic landscape-related properties. 2. Using butterflies as a model system, the following questions were addressed: (i) given similar extrinsic factors, which intrinsic species trait(s) explain dispersal ability? (ii) can one of these traits be used as a proxy for dispersal ability? (iii) the effect of interactions between the traits, and phylogenetic relatedness, on dispersal ability. 3. Four data sets, using different measures of dispersal, were compiled from published literature. The first data set uses mean dispersal distances from capture-mark-recapture studies, and the other three use mobility indices. Data for six traits that can potentially affect dispersal ability were collected: wingspan, larval host plant specificity, adult habitat specificity, mate location strategy, voltinism and flight period duration. Each data set was subjected to both unifactorial, and multifactorial, phylogenetically controlled analyses. 4. Among the factors considered, wingspan was the most important determinant of dispersal ability, although the predictive powers of regression models were low. Voltinism and flight period duration also affect dispersal ability, especially in case of temperate species. Interactions between the factors did not affect dispersal ability, and phylogenetic relatedness was significant in one data set. 5. While using wingspan as the only proxy for dispersal ability maybe problematic, it is usually the only easily accessible species-specific trait for a large number of species. It can thus be a satisfactory proxy when carefully interpreted, especially for analyses involving many species from all across the world.

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Expanding energy access to the rural population of India presents a critical challenge for its government. The presence of 364 million people without access to electricity and 726 million who rely on biomass for cooking indicate both the failure of past policies and programs, and the need for a radical redesign of the current system. We propose an integrated implementation framework with recommendations for adopting business principles with innovative institutional, regulatory, financing and delivery mechanisms. The framework entails establishment of rural energy access authorities and energy access funds, both at the national and regional levels, to be empowered with enabling regulatory policies, capital resources and the support of multi-stakeholder partnership. These institutions are expected to design, lead, manage and monitor the rural energy interventions. At the other end, trained entrepreneurs would be expected to establish bioenergy-based micro-enterprises that will produce and distribute energy carriers to rural households at an affordable cost. The ESCOs will function as intermediaries between these enterprises and the international carbon market both in aggregating carbon credits and in trading them under CDM. If implemented, such a program could address the challenges of rural energy empowerment by creating access to modern energy carriers and climate change mitigation. (C) 2011 Elsevier Ltd. All rights reserved.

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We address the problem of pricing defaultable bonds in a Markov modulated market. Using Merton's structural approach we show that various types of defaultable bonds are combination of European type contingent claims. Thus pricing a defaultable bond is tantamount to pricing a contingent claim in a Markov modulated market. Since the market is incomplete, we use the method of quadratic hedging and minimal martingale measure to derive locally risk minimizing derivative prices, hedging strategies and the corresponding residual risks. The price of defaultable bonds are obtained as solutions to a system of PDEs with weak coupling subject to appropriate terminal and boundary conditions. We solve the system of PDEs numerically and carry out a numerical investigation for the defaultable bond prices. We compare their credit spreads with some of the existing models. We observe higher spreads in the Markov modulated market. We show how business cycles can be easily incorporated in the proposed framework. We demonstrate the impact on spreads of the inclusion of rare states that attempt to capture a tight liquidity situation. These states are characterized by low risk-free interest rate, high payout rate and high volatility.

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Purpose: To optimize the data-collection strategy for diffuse optical tomography and to obtain a set of independent measurements among the total measurements using the model based data-resolution matrix characteristics. Methods: The data-resolution matrix is computed based on the sensitivity matrix and the regularization scheme used in the reconstruction procedure by matching the predicted data with the actual one. The diagonal values of data-resolution matrix show the importance of a particular measurement and the magnitude of off-diagonal entries shows the dependence among measurements. Based on the closeness of diagonal value magnitude to off-diagonal entries, the independent measurements choice is made. The reconstruction results obtained using all measurements were compared to the ones obtained using only independent measurements in both numerical and experimental phantom cases. The traditional singular value analysis was also performed to compare the results obtained using the proposed method. Results: The results indicate that choosing only independent measurements based on data-resolution matrix characteristics for the image reconstruction does not compromise the reconstructed image quality significantly, in turn reduces the data-collection time associated with the procedure. When the same number of measurements (equivalent to independent ones) are chosen at random, the reconstruction results were having poor quality with major boundary artifacts. The number of independent measurements obtained using data-resolution matrix analysis is much higher compared to that obtained using the singular value analysis. Conclusions: The data-resolution matrix analysis is able to provide the high level of optimization needed for effective data-collection in diffuse optical imaging. The analysis itself is independent of noise characteristics in the data, resulting in an universal framework to characterize and optimize a given data-collection strategy. (C) 2012 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4736820]

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Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.

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Many meteorological phenomena occur at different locations simultaneously. These phenomena vary temporally and spatially. It is essential to track these multiple phenomena for accurate weather prediction. Efficient analysis require high-resolution simulations which can be conducted by introducing finer resolution nested simulations, nests at the locations of these phenomena. Simultaneous tracking of these multiple weather phenomena requires simultaneous execution of the nests on different subsets of the maximum number of processors for the main weather simulation. Dynamic variation in the number of these nests require efficient processor reallocation strategies. In this paper, we have developed strategies for efficient partitioning and repartitioning of the nests among the processors. As a case study, we consider an application of tracking multiple organized cloud clusters in tropical weather systems. We first present a parallel data analysis algorithm to detect such clouds. We have developed a tree-based hierarchical diffusion method which reallocates processors for the nests such that the redistribution cost is less. We achieve this by a novel tree reorganization approach. We show that our approach exhibits up to 25% lower redistribution cost and 53% lesser hop-bytes than the processor reallocation strategy that does not consider the existing processor allocation.

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The current work addresses the use of producer gas, a bio-derived gaseous alternative fuel, in engines designed for natural gas, derived from diesel engine frames. Impact of the use of producer gas on the general engine performance with specific focus on turbo-charging is addressed. The operation of a particular engine frame with diesel, natural gas and producer gas indicates that the peak load achieved is highest with diesel fuel (in compression ignition mode) followed by natural gas and producer gas (both in spark ignite mode). Detailed analysis of the engine power de-rating on fuelling with natural gas and producer gas indicates that the change in compression ratio (migration from compression to spark ignited mode), difference in mixture calorific value and turbocharger mismatch are the primary contributing factors. The largest de-rating occurs due to turbocharger mismatch. Turbocharger selection and optimization is identified as the strategy to recover the non-thermodynamic power loss, identified as the recovery potential (the loss due to mixture calorific value and turbocharger mismatch) on operating the engine with a fuel different from the base fuel. A turbocharged after-cooled six cylinder, 5.9 l, 90 kWe (diesel rating) engine (12.2 bar BMEP) is available commercially as a naturally aspirated natural gas engine delivering a peak load of 44.0 kWe (6.0 bar BMEP). The engine delivers a load of 27.3 kWe with producer gas under naturally aspirated mode. On charge boosting the engine with a turbocharger similar in configuration to the diesel engine turbocharger, the peak load delivered with producer gas is 36 kWe (4.8 bar BMEP) indicating a de-rating of about 60% over the baseline diesel mode. Estimation of knock limited peak load for producer gas-fuelled operation on the engine frame using a Wiebe function-based zero-dimensional code indicates a knock limited peak load of 76 kWe, indicating the potential to recover about 40 kWe. As a part of the recovery strategy, optimizing the ignition timing for maximum brake torque based on both spark sweep tests and established combustion descriptors and engine-turbocharger matching for producer gas-fuelled operation resulted in a knock limited peak load of 72.8 kWe (9.9 bar BMEP) at a compressor pressure ratio of 2.30. The de-rating of about 17.0 kWe compared to diesel rating is attributed to the reduction in compression ratio. With load recovery, the specific biomass consumption reduces from 1.2 kg/kWh to 1.0 kg/kWh, an improvement of over 16% while the engine thermal efficiency increases from 28% to 32%. The thermodynamic analysis of the compressor and the turbine indicates an isentropic efficiency of 74.5% and 73%, respectively.