965 resultados para SRM module


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A set of sufficient conditions to construct lambda-real symbol Maximum Likelihood (ML) decodable STBCs have recently been provided by Karmakar et al. STBCs satisfying these sufficient conditions were named as Clifford Unitary Weight (CUW) codes. In this paper, the maximal rate (as measured in complex symbols per channel use) of CUW codes for lambda = 2(a), a is an element of N is obtained using tools from representation theory. Two algebraic constructions of codes achieving this maximal rate are also provided. One of the constructions is obtained using linear representation of finite groups whereas the other construction is based on the concept of right module algebra over non-commutative rings. To the knowledge of the authors, this is the first paper in which matrices over non-commutative rings is used to construct STBCs. An algebraic explanation is provided for the 'ABBA' construction first proposed by Tirkkonen et al and the tensor product construction proposed by Karmakar et al. Furthermore, it is established that the 4 transmit antenna STBC originally proposed by Tirkkonen et al based on the ABBA construction is actually a single complex symbol ML decodable code if the design variables are permuted and signal sets of appropriate dimensions are chosen.

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The emergence of strains of Plasmodium falciparum resistant to the commonly used antimalarials warrants the development of new antimalarial agents. The discovery of type II fatty acid synthase (FAS) in Plasmodium distinct from the FAS in its human host (type I FAS) opened up new avenues for the development of novel antimalarials. The process of fatty acid synthesis takes place by iterative elongation of butyryl-acyl carrier protein (butyryl-ACP) by two carbon units, with the successive action of four enzymes constituting the elongation module of FAS until the desired acyl length is obtained. The study of the fatty acid synthesis machinery of the parasite inside the red blood cell culture has always been a challenging task. Here, we report the in vitro reconstitution of the elongation module of the FAS of malaria parasite involving all four enzymes, FabB/F (β-ketoacyl-ACP synthase), FabG (β-ketoacyl-ACP reductase), FabZ (β-ketoacyl-ACP dehydratase), and FabI (enoyl-ACP reductase), and its analysis by matrix-assisted laser desorption-time of flight mass spectrometry (MALDI-TOF MS). That this in vitro systems approach completely mimics the in vivo machinery is confirmed by the distribution of acyl products. Using known inhibitors of the enzymes of the elongation module, cerulenin, triclosan, NAS-21/91, and (–)-catechin gallate, we demonstrate that accumulation of intermediates resulting from the inhibition of any of the enzymes can be unambiguously followed by MALDI-TOF MS. Thus, this work not only offers a powerful tool for easier and faster throughput screening of inhibitors but also allows for the study of the biochemical properties of the FAS pathway of the malaria parasite.

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The emergence of strains of Plasmodium falciparum resistant to the commonly used antimalarials warrants the development of new antimalarial agents. The discovery of type II fatty acid synthase (FAS) in Plasmodium distinct from the FAS in its human host (type I FAS) opened up new avenues for the development of novel antimalarials. The process of fatty acid synthesis takes place by iterative elongation of butyryl-acyl carrier protein (butyryl-ACP) by two carbon units, with the successive action of four enzymes constituting the elongation module of FAS until the desired acyl length is obtained. The study of the fatty acid synthesis machinery of the parasite inside the red blood cell culture has always been a challenging task. Here, we report the in vitro reconstitution of the elongation module of the FAS of malaria parasite involving all four enzymes, FabB/F (β-ketoacyl-ACP synthase), FabG (β-ketoacyl-ACP reductase), FabZ (β-ketoacyl-ACP dehydratase), and FabI (enoyl-ACP reductase), and its analysis by matrix-assisted laser desorption-time of flight mass spectrometry (MALDI-TOF MS). That this in vitro systems approach completely mimics the in vivo machinery is confirmed by the distribution of acyl products. Using known inhibitors of the enzymes of the elongation module, cerulenin, triclosan, NAS-21/91, and (–)-catechin gallate, we demonstrate that accumulation of intermediates resulting from the inhibition of any of the enzymes can be unambiguously followed by MALDI-TOF MS. Thus, this work not only offers a powerful tool for easier and faster throughput screening of inhibitors but also allows for the study of the biochemical properties of the FAS pathway of the malaria parasite.

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Background: MHC/HLA class II molecules are important components of the immune system and play a critical role in processes such as phagocytosis. Understanding peptide recognition properties of the hundreds of MHC class II alleles is essential to appreciate determinants of antigenicity and ultimately to predict epitopes. While there are several methods for epitope prediction, each differing in their success rates, there are no reports so far in the literature to systematically characterize the binding sites at the structural level and infer recognition profiles from them. Results: Here we report a new approach to compare the binding sites of MHC class II molecules using their three dimensional structures. We use a specifically tuned version of our recent algorithm, PocketMatch. We show that our methodology is useful for classification of MHC class II molecules based on similarities or differences among their binding sites. A new module has been used to define binding sites in MHC molecules. Comparison of binding sites of 103 MHC molecules, both at the whole groove and individual sub-pocket levels has been carried out, and their clustering patterns analyzed. While clusters largely agree with serotypic classification, deviations from it and several new insights are obtained from our study. We also present how differences in sub-pockets of molecules associated with a pair of autoimmune diseases, narcolepsy and rheumatoid arthritis, were captured by PocketMatch(13). Conclusion: The systematic framework for understanding structuralvariations in MHC class II molecules enables large scale comparison of binding grooves and sub-pockets, which is likely to have direct implications towards predicting epitopes and understanding peptide binding preferences.

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16-electrode phantoms are developed and studied with a simple instrumentation developed for Electrical Impedance Tomography. An analog instrumentation is developed with a sinusoidal current generator and signal conditioner circuit. Current generator is developed withmodified Howland constant current source fed by a voltage controlled oscillator and the signal conditioner circuit consisting of an instrumentation amplifier and a narrow band pass filter. Electronic hardware is connected to the electrodes through a DIP switch based multiplexer module. Phantoms with different electrode size and position are developed and the EIT forward problem is studied using the forward solver. A low frequency low magnitude sinusoidal current is injected to the surface electrodes surrounding the phantom boundary and the differential potential is measured by a digital multimeter. Comparing measured potential with the simulated data it is intended to reduce the measurement error and an optimum phantom geometry is suggested. Result shows that the common mode electrode reduces the common mode error of the EIT electronics and reduces the error potential in the measured data. Differential potential is reduced up to 67 mV at the voltage electrode pair opposite to the current electrodes. Offset potential is measured and subtracted from the measured data for further correction. It is noticed that the potential data pattern depends on the electrode width and the optimum electrode width is suggested. It is also observed that measured potential becomes acceptable with a 20 mm solution column above and below the electrode array level.

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Background: MHC/HLA class II molecules are important components of the immune system and play a critical role in processes such as phagocytosis. Understanding peptide recognition properties of the hundreds of MHC class II alleles is essential to appreciate determinants of antigenicity and ultimately to predict epitopes. While there are several methods for epitope prediction, each differing in their success rates, there are no reports so far in the literature to systematically characterize the binding sites at the structural level and infer recognition profiles from them. Results: Here we report a new approach to compare the binding sites of MHC class II molecules using their three dimensional structures. We use a specifically tuned version of our recent algorithm, PocketMatch. We show that our methodology is useful for classification of MHC class II molecules based on similarities or differences among their binding sites. A new module has been used to define binding sites in MHC molecules. Comparison of binding sites of 103 MHC molecules, both at the whole groove and individual sub-pocket levels has been carried out, and their clustering patterns analyzed. While clusters largely agree with serotypic classification, deviations from it and several new insights are obtained from our study. We also present how differences in sub-pockets of molecules associated with a pair of autoimmune diseases, narcolepsy and rheumatoid arthritis, were captured by PocketMatch(13). Conclusion: The systematic framework for understanding structural variations in MHC class II molecules enables large scale comparison of binding grooves and sub-pockets, which is likely to have direct implications towards predicting epitopes and understanding peptide binding preferences.

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An approximate dynamic programming (ADP) based neurocontroller is developed for a heat transfer application. Heat transfer problem for a fin in a car's electronic module is modeled as a nonlinear distributed parameter (infinite-dimensional) system by taking into account heat loss and generation due to conduction, convection and radiation. A low-order, finite-dimensional lumped parameter model for this problem is obtained by using Galerkin projection and basis functions designed through the 'Proper Orthogonal Decomposition' technique (POD) and the 'snap-shot' solutions. A suboptimal neurocontroller is obtained with a single-network-adaptive-critic (SNAC). Further contribution of this paper is to develop an online robust controller to account for unmodeled dynamics and parametric uncertainties. A weight update rule is presented that guarantees boundedness of the weights and eliminates the need for persistence of excitation (PE) condition to be satisfied. Since, the ADP and neural network based controllers are of fairly general structure, they appear to have the potential to be controller synthesis tools for nonlinear distributed parameter systems especially where it is difficult to obtain an accurate model.

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One of the foremost design considerations in microelectronics miniaturization is the use of embedded passives which provide practical solution. In a typical circuit, over 80 percent of the electronic components are passives such as resistors, inductors, and capacitors that could take up to almost 50 percent of the entire printed circuit board area. By integrating passive components within the substrate instead of being on the surface, embedded passives reduce the system real estate, eliminate the need for discrete and assembly, enhance electrical performance and reliability, and potentially reduce the overall cost. Moreover, it is lead free. Even with these advantages, embedded passive technology is at a relatively immature stage and more characterization and optimization are needed for practical applications leading to its commercialization.This paper presents an entire process from design and fabrication to electrical characterization and reliability test of embedded passives on multilayered microvia organic substrate. Two test vehicles focusing on resistors and capacitors have been designed and fabricated. Embedded capacitors in this study are made with polymer/ceramic nanocomposite (BaTiO3) material to take advantage of low processing temperature of polymers and relatively high dielectric constant of ceramics and the values of these capacitors range from 50 pF to 1.5 nF with capacitance per area of approximately 1.5 nF/cm(2). Limited high frequency measurement of these capacitors was performed. Furthermore, reliability assessments of thermal shock and temperature humidity tests based on JEDEC standards were carried out. Resistors used in this work have been of three types: 1) carbon ink based polymer thick film (PTF), 2) resistor foils with known sheet resistivities which are laminated to printed wiring board (PWB) during a sequential build-up (SBU) process and 3) thin-film resistor plating by electroless method. Realization of embedded resistors on conventional board-level high-loss epoxy (similar to 0.015 at 1 GHz) and proposed low-loss BCB dielectric (similar to 0.0008 at > 40 GHz) has been explored in this study. Ni-P and Ni-W-P alloys were plated using conventional electroless plating, and NiCr and NiCrAlSi foils were used for the foil transfer process. For the first time, Benzocyclobutene (BCB) has been proposed as a board level dielectric for advanced System-on-Package (SOP) module primarily due to its attractive low-loss (for RF application) and thin film (for high density wiring) properties.Although embedded passives are more reliable by eliminating solder joint interconnects, they also introduce other concerns such as cracks, delamination and component instability. More layers may be needed to accommodate the embedded passives, and various materials within the substrate may cause significant thermo -mechanical stress due to coefficient of thermal expansion (CTE) mismatch. In this work, numerical models of embedded capacitors have been developed to qualitatively examine the effects of process conditions and electrical performance due to thermo-mechanical deformations.Also, a prototype working product with the board level design including features of embedded resistors and capacitors are underway. Preliminary results of these are presented.

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A fuzzy system is developed using a linearized performance model of the gas turbine engine for performing gas turbine fault isolation from noisy measurements. By using a priori information about measurement uncertainties and through design variable linking, the design of the fuzzy system is posed as an optimization problem with low number of design variables which can be solved using the genetic algorithm in considerably low amount of computer time. The faults modeled are module faults in five modules: fan, low pressure compressor, high pressure compressor, high pressure turbine and low pressure turbine. The measurements used are deviations in exhaust gas temperature, low rotor speed, high rotor speed and fuel flow from a base line 'good engine'. The genetic fuzzy system (GFS) allows rapid development of the rule base if the fault signatures and measurement uncertainties change which happens for different engines and airlines. In addition, the genetic fuzzy system reduces the human effort needed in the trial and error process used to design the fuzzy system and makes the development of such a system easier and faster. A radial basis function neural network (RBFNN) is also used to preprocess the measurements before fault isolation. The RBFNN shows significant noise reduction and when combined with the GFS leads to a diagnostic system that is highly robust to the presence of noise in data. Showing the advantage of using a soft computing approach for gas turbine diagnostics.

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Massively parallel SIMD computing is applied to obtain an order of magnitude improvement in the executional speed of an important algorithm in VLSI design automation. The physical design of a VLSI circuit involves logic module placement as a subtask. The paper is concerned with accelerating the well known Min-cut placement technique for logic cell placement. The inherent parallelism of the Min-cut algorithm is identified, and it is shown that a parallel machine based on the efficient execution of the placement procedure.

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Fracture behaviour of notched and un-notched plain concrete slender beams subjected to three-point or four-point bending is analyzed through a one-dimensional model, also called Softening Beam Model. Fundamental equations of equilibrium are used to develop the model. The influence of structural size in altering the fracture mode from brittle fracture to plastic collapse is explained through the stress distribution across the uncracked ligament obtained by varying the strain softening modulus. It is found that at the onset of fracture instability, stress at the crack tip is equal to zero. The maximum load and fracture load are found to be different and a unique value for the fracture load is obtained. It is shown that the length of the fracture process zone depends on the value of the strain softening modulus. Theoretical limits for fracture process zone length are also calculated. Several nonlinear fracture parameters, such as, crack tip opening displacement, crack mouth opening displacement and fracture energy are computed for a wide variety of beam specimens reported in the literature and are found to compare very well with experimental and theoretical results. It is demonstrated that by following a simple procedure, both pre-peak and post-peak portions of load versus crack mouth opening displacement curve can be obtained quite accurately. Further, a simple procedure to calculate the maximum load is also developed. The predicted values of maximum load are found to agree well with the experimental values. The Softening Beam Model (SBM), proposed in this investigation is very simple and is based on rational considerations. It can completely describe the fracture process from the beginning of formation of the fracture process zone till the onset of fracture instability.A l'aide d'un modèle unidimensionnel dit ldquoSoftening Beam Modelrdquo (SBM), on analyse le comportement à rupture de poutres élancées pleines entaillées ou non, soumises en flexion en trois ou quatre points. Des équations fondamentales d'équilibre sont utilisées pour développer le modèle. On explique l'influence de la taille du composant sur l'altération du mode de rupture en rupture fragile et en effondrement plastique par la distribution par la distribution des contraintes sur le ligament non fissuré lorsque varie le module d'adoucissement. On trouve que la contrainte à l'extrémité de la fissure est nulle est nulle au début de l'instabilité de la rupture. La charge maximum et la charge à la rupture sont trouvées différentes, et on obtient une valeur unique de la charge à la rupture. On montre que la longueur de la zone concernée par le processus de rupture d'pend de la valeur du module d'adoucissement. On calcule également les limites théoriques de longueur de cette zone. Divers paramètres de rupture non linéaire sont calculés pour une large gamme d'éprouvettes en poutres reprises dans la littérature; on trouve qu'il existe une bonne concordance avec les résultats expérimentaux et théoriques. On démontre qu'en suivant une procédure simple on peut obtenir avec une bonne précision la courbe reliant les portions avant et après le pic de sollicitation en fonction du COD de la fissure. En outre, on développe une procédure simple pour calculer la charge maximum. Les valeurs prédites sont en bon accord avec les valeurs expérimentales. Le modèle SBM proposé est très simple et est basé sur des considérations rationnelles. Il est susceptible de décrire complètement le processus de rupture depuis le début de la formation de la zone intéressée jusqu'à l'amorçage de la rupture instable.

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Abstract. Methane emissions from natural wetlands and rice paddies constitute a large proportion of atmospheric methane, but the magnitude and year-to-year variation of these methane sources is still unpredictable. Here we describe and evaluate the integration of a methane biogeochemical model (CLM4Me; Riley et al., 2011) into the Community Land Model 4.0 (CLM4CN) in order to better explain spatial and temporal variations in methane emissions. We test new functions for soil pH and redox potential that impact microbial methane production in soils. We also constrain aerenchyma in plants in always-inundated areas in order to better represent wetland vegetation. Satellite inundated fraction is explicitly prescribed in the model because there are large differences between simulated fractional inundation and satellite observations. A rice paddy module is also incorporated into the model, where the fraction of land used for rice production is explicitly prescribed. The model is evaluated at the site level with vegetation cover and water table prescribed from measurements. Explicit site level evaluations of simulated methane emissions are quite different than evaluating the grid cell averaged emissions against available measurements. Using a baseline set of parameter values, our model-estimated average global wetland emissions for the period 1993–2004 were 256 Tg CH4 yr−1, and rice paddy emissions in the year 2000 were 42 Tg CH4 yr−1. Tropical wetlands contributed 201 Tg CH4 yr−1, or 78 % of the global wetland flux. Northern latitude (>50 N) systems contributed 12 Tg CH4 yr−1. We expect this latter number may be an underestimate due to the low high-latitude inundated area captured by satellites and unrealistically low high-latitude productivity and soil carbon predicted by CLM4. Sensitivity analysis showed a large range (150–346 Tg CH4 yr−1) in predicted global methane emissions. The large range was sensitive to: (1) the amount of methane transported through aerenchyma, (2) soil pH (± 100 Tg CH4 yr−1), and (3) redox inhibition (± 45 Tg CH4 yr−1).

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The use of the shear wave velocity data as a field index for evaluating the liquefaction potential of sands is receiving increased attention because both shear wave velocity and liquefaction resistance are similarly influenced by many of the same factors such as void ratio, state of stress, stress history and geologic age. In this paper, the potential of support vector machine (SVM) based classification approach has been used to assess the liquefaction potential from actual shear wave velocity data. In this approach, an approximate implementation of a structural risk minimization (SRM) induction principle is done, which aims at minimizing a bound on the generalization error of a model rather than minimizing only the mean square error over the data set. Here SVM has been used as a classification tool to predict liquefaction potential of a soil based on shear wave velocity. The dataset consists the information of soil characteristics such as effective vertical stress (sigma'(v0)), soil type, shear wave velocity (V-s) and earthquake parameters such as peak horizontal acceleration (a(max)) and earthquake magnitude (M). Out of the available 186 datasets, 130 are considered for training and remaining 56 are used for testing the model. The study indicated that SVM can successfully model the complex relationship between seismic parameters, soil parameters and the liquefaction potential. In the model based on soil characteristics, the input parameters used are sigma'(v0), soil type. V-s, a(max) and M. In the other model based on shear wave velocity alone uses V-s, a(max) and M as input parameters. In this paper, it has been demonstrated that Vs alone can be used to predict the liquefaction potential of a soil using a support vector machine model. (C) 2010 Elsevier B.V. All rights reserved.

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In this paper we associate a new geometric invariant to the space of fiat connections on a G (= SU(2))-bundle on a compact Riemann surface M and relate it tcr the symplectic structure on the space Hom(pi(1)(M), G)/G consisting of representations of the fundamental group pi(1)(M) Of M into G module the conjugate action of G on representations.

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An integrated model is developed, based on seasonal inputs of reservoir inflow and rainfall in the irrigated area, to determine the optimal reservoir release policies and irrigation allocations to multiple crops. The model is conceptually made up of two modules, Module 1 is an intraseasonal allocation model to maximize the sum of relative yields of all crops, for a given state of the system, using linear programming (LP). The module takes into account reservoir storage continuity, soil moisture balance, and crop root growth with time. Module 2 is a seasonal allocation model to derive the steady state reservoir operating policy using stochastic dynamic programming (SDP). Reservoir storage, seasonal inflow, and seasonal rainfall are the state variables in the SDP. The objective in SDP is to maximize the expected sum of relative yields of all crops in a year. The results of module 1 and the transition probabilities of seasonal inflow and rainfall form the input for module 2. The use of seasonal inputs coupled with the LP-SDP solution strategy in the present formulation facilitates in relaxing the limitations of an earlier study, while affecting additional improvements. The model is applied to an existing reservoir in Karnataka State, India.