166 resultados para SELECTION PRINCIPLES


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In this letter, we quantify the transmit diversity order of the SM system operating in a closed-loop scenario. Specifically, the SM system relying on Euclidean distance based antenna subset selection (EDAS) is considered and the achievable diversity gain is evaluated. Furthermore, the resultant trade-off between the achievable diversity gain and switching gain is studied. Simulation results confirm our theoretical results. Specifically, at a symbol error rate of about 10(-4) the signal-to-noise ratio gain achieved by EDAS is about 7 dB in case of 16-QAM and about 5 dB in case of 64-QAM.

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Background: Computational protein design is a rapidly maturing field within structural biology, with the goal of designing proteins with custom structures and functions. Such proteins could find widespread medical and industrial applications. Here, we have adapted algorithms from the Rosetta software suite to design much larger proteins, based on ideal geometric and topological criteria. Furthermore, we have developed techniques to incorporate symmetry into designed structures. For our first design attempt, we targeted the (alpha/beta)(8) TIM barrel scaffold. We gained novel insights into TIM barrel folding mechanisms from studying natural TIM barrel structures, and from analyzing previous TIM barrel design attempts. Methods: Computational protein design and analysis was performed using the Rosetta software suite and custom scripts. Genes encoding all designed proteins were synthesized and cloned on the pET20-b vector. Standard circular dichroism and gel chromatographic experiments were performed to determine protein biophysical characteristics. 1D NMR and 2D HSQC experiments were performed to determine protein structural characteristics. Results: Extensive protein design simulations coupled with ab initio modeling yielded several all-atom models of ideal, 4-fold symmetric TIM barrels. Four such models were experimentally characterized. The best designed structure (Symmetrin-1) contained a polar, histidine-rich pore, forming an extensive hydrogen bonding network. Symmetrin-1 was easily expressed and readily soluble. It showed circular dichroism spectra characteristic of well-folded alpha/beta proteins. Temperature melting experiments revealed cooperative and reversible unfolding, with a T-m of 44 degrees C and a Gibbs free energy of unfolding (Delta G degrees) of 8.0 kJ/mol. Urea denaturing experiments confirmed these observations, revealing a C-m of 1.6 M and a Delta G degrees of 8.3 kJ/mol. Symmetrin-1 adopted a monomeric conformation, with an apparent molecular weight of 32.12 kDa, and displayed well resolved 1D-NMR spectra. However, the HSQC spectrum revealed somewhat molten characteristics. Conclusions: Despite the detection of molten characteristics, the creation of a soluble, cooperatively folding protein represents an advancement over previous attempts at TIM barrel design. Strategies to further improve Symmetrin-1 are elaborated. Our techniques may be used to create other large, internally symmetric proteins.

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Cooperative relaying combined with selection exploits spatial diversity to significantly improve the performance of interference-constrained secondary users in an underlay cognitive radio (CR) network. However, unlike conventional relaying, the state of the links between the relay and the primary receiver affects the choice of the relay. Further, while the optimal amplify-and-forward (AF) relay selection rule for underlay CR is well understood for the peak interference-constraint, this is not so for the less conservative average interference constraint. For the latter, we present three novel AF relay selection (RS) rules, namely, symbol error probability (SEP)-optimal, inverse-of-affine (IOA), and linear rules. We analyze the SEPs of the IOA and linear rules and also develop a novel, accurate approximation technique for analyzing the performance of AF relays. Extensive numerical results show that all the three rules outperform several RS rules proposed in the literature and generalize the conventional AF RS rule.

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The crystallization of 28 binary and ternary cocrystals of quercetin with dibasic coformers is analyzed in terms of a combinatorial selection from a solution of preferred molecular conformations and supramolecular synthons. The crystal structures are characterized by distinctive O-H center dot center dot center dot N and O-H center dot center dot center dot O based synthons and are classified as nonporous, porous and helical. Variability in molecular conformation and synthon structure led to an increase in the energetic and structural space around the crystallization event. This space is the crystal structure landscape of the compound and is explored by fine-tuning the experimental conditions of crystallization. In the landscape context, we develop a strategy for the isolation of ternary cocrystals with the use of auxiliary template molecules to reduce the molecular and supramolecular `confusion' that is inherent in a molecule like quercetin. The absence of concomitant polymorphism in this study highlights the selectivity in conformation and synthon choice from the virtual combinatorial library in solution.

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Flexray is a high speed communication protocol designed for distributive control in automotive control applications. Control performance not only depends on the control algorithm but also on the scheduling constraints in communication. A balance between the control performance and communication constraints must required for the choice of the sampling rates of the control loops in a node. In this paper, an optimum sampling period of control loops to minimize the cost function, satisfying the scheduling constraints is obtained. An algorithm to obtain the delay in service of each task in a node of the control loop in the hyper period has been also developed. (C) 2015 The Authors. Published by Elsevier B.V.

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For a multilayered specimen, the back-scattered signal in frequency-domain optical-coherence tomography (FDOCT) is expressible as a sum of cosines, each corresponding to a change of refractive index in the specimen. Each of the cosines represent a peak in the reconstructed tomogram. We consider a truncated cosine series representation of the signal, with the constraint that the coefficients in the basis expansion be sparse. An l(2) (sum of squared errors) data error is considered with an l(1) (summation of absolute values) constraint on the coefficients. The optimization problem is solved using Weiszfeld's iteratively reweighted least squares (IRLS) algorithm. On real FDOCT data, improved results are obtained over the standard reconstruction technique with lower levels of background measurement noise and artifacts due to a strong l(1) penalty. The previous sparse tomogram reconstruction techniques in the literature proposed collecting sparse samples, necessitating a change in the data capturing process conventionally used in FDOCT. The IRLS-based method proposed in this paper does not suffer from this drawback.

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This paper considers the problem of receive antenna selection (AS) in a multiple-antenna communication system having a single radio-frequency (RF) chain. The AS decisions are based on noisy channel estimates obtained using known pilot symbols embedded in the data packets. The goal here is to minimize the average packet error rate (PER) by exploiting the known temporal correlation of the channel. As the underlying channels are only partially observed using the pilot symbols, the problem of AS for PER minimization is cast into a partially observable Markov decision process (POMDP) framework. Under mild assumptions, the optimality of a myopic policy is established for the two-state channel case. Moreover, two heuristic AS schemes are proposed based on a weighted combination of the estimated channel states on the different antennas. These schemes utilize the continuous valued received pilot symbols to make the AS decisions, and are shown to offer performance comparable to the POMDP approach, which requires one to quantize the channel and observations to a finite set of states. The performance improvement offered by the POMDP solution and the proposed heuristic solutions relative to existing AS training-based approaches is illustrated using Monte Carlo simulations.

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Selection of relevant features is an open problem in Brain-computer interfacing (BCI) research. Sometimes, features extracted from brain signals are high dimensional which in turn affects the accuracy of the classifier. Selection of the most relevant features improves the performance of the classifier and reduces the computational cost of the system. In this study, we have used a combination of Bacterial Foraging Optimization and Learning Automata to determine the best subset of features from a given motor imagery electroencephalography (EEG) based BCI dataset. Here, we have employed Discrete Wavelet Transform to obtain a high dimensional feature set and classified it by Distance Likelihood Ratio Test. Our proposed feature selector produced an accuracy of 80.291% in 216 seconds.

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The structures of nine independent crystals of bitter gourd seed lectin (BGSL), a non-toxic homologue of type II RIPs, and its sugar complexes have been determined. The four-chain, two-fold symmetric, protein is made up of two identical two-chain modules, each consisting of a catalytic chain and a lectin chain, connected by a disulphide bridge. The lectin chain is made up of two domains. Each domain carries a carbohydrate binding site in type II RIPs of known structure. BGSL has a sugar binding site only on one domain, thus impairing its interaction at the cell surface. The adenine binding site in the catalytic chain is defective. Thus, defects in sugar binding as well as adenine binding appear to contribute to the non-toxicity of the lectin. The plasticity of the molecule is mainly caused by the presence of two possible well defined conformations of a surface loop in the lectin chain. One of them is chosen in the sugar complexes, in a case of conformational selection, as the chosen conformation facilitates an additional interaction with the sugar, involving an arginyl residue in the loop. The N-glycosylation of the lectin involves a plant-specific glycan while that in toxic type II RIPs of known structure involves a glycan which is animal as well as plant specific.

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The electronic structure and hydrogen storage capability of Yttrium-doped BNNTs has been theoretically investigated using first principles density functional theory (DFT). Yttrium atom prefers the hollow site in the center of the hexagonal ring with a binding energy of 0.8048eV. Decorating by Y makes the system half-metallic and magnetic with a magnetic moment of 1.0 mu(B). Y decorated Boron-Nitride (8,0) nanotube can adsorb up to five hydrogen molecules whose average binding energy is computed as 0.5044eV. All the hydrogen molecules are adsorbed with an average desorption temperature of 644.708 K. Taking that the Y atoms can be placed only in alternate hexagons, the implied wt% comes out to be 5.31%, a relatively acceptable value for hydrogen storage materials. Thus, this system can serve as potential hydrogen storage medium.

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Ropalidia marginata is a primitively eusocial wasp widely distributed in peninsular India. Although solitary females found a small proportion of nests, the vast majority of new nests are founded by small groups of females. In suchmultiple foundress nests, a single dominant female functions as the queen and lays eggs, while the rest function as sterile workers and care for the queen's brood. Previous attempts to understand the evolution of social behaviour and altruism in this species have employed inclusive fitness theory (kin selection) as a guiding framework. Although inclusive fitness theory is quite successful in explaining the high propensity of the wasps to found nests in groups, several features of their social organization suggest that forces other than kin selection may also have played a significant role in the evolution of this species. These features include lowering of genetic relatedness owing to polyandry and serial polygyny, nest foundation by unrelated individuals, acceptance of young non-nest-mates, a combination of well-developed nest-mate recognition and lack of intra-colony kin recognition, a combination of meek and docile queens and a decentralized self-organized work force, long reproductive queues with cryptic heir designates and conflict-free queen succession, all resulting in extreme intra-colony cooperation and inter-colony conflict.

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We investigate the electronic and thermal transport properties of bulk MX2 compounds (M = Zr, Hf and X = S, Se) by first-principles calculations and semi-classical Boltzmann transport theory. The band structure shows the confinement of heavy and light bands along the out of plane and in-plane directions, respectively. This results in high electrical conductivity (sigma) and large thermopower leading to a high power factor (S-2 sigma) for moderate n-type doping. The phonon dispersion demonstrates low frequency flat acoustical modes, which results in low group velocities (v(g)). Consequently, lowering the lattice thermal conductivity (kappa(latt)) below 2 W/m K. Low kappa(latt) combined with high power factor results in ZT > 0.8 for all the bulk MX2 compounds at high temperature of 1200 K. In particular, the ZT(max) of HfSe2 exceeds 1 at 1400 K. Our results show that Hf/Zr based dichalcogenides are very promising for high temperature thermoelectric application. (C) 2015 AIP Publishing LLC.

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A new method of selection of time-to-go (t(go)) for Generalized Vector Explicit Guidance (GENEX) law have been proposed in this paper. t(go) is known to be an important parameter in the control and cost function of GENEX guidance law. In this paper the formulation has been done to find an optimal value of t(go) that minimizes the performance cost. Mechanization of GENEX with this optimal t(go) reduces the lateral acceleration demand and consequently increases the range of the interceptor. This new formulation of computing t(go) comes in closed form and thus it can be implemented onboard. This new formulation is applied in the terminal phase of an surface-to-air interceptor for an angle constrained engagement. Results generated by simulation justify the use of optimal t(go).

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Tb0.3Dy0.7Fe1.95 alloy was directionally solidified by using a modified Bridgman technique at a wide range of growth rates of 5 to 100 cm/h. The directionally grown samples exhibited plane front solidification morphology up to a growth rate of 90 cm/h. Typical island banding feature was observed closer to the chilled end, which eventually gave rise to irregular peritectic coupled growth (PCG). The PCG gained prominence with an increase in the growth rate. The texture study revealed formation of strong aOE (c) 311 > texture in a lower growth rate regime, aOE (c) 110 > and ``rotated aOE (c) 110 > aEuroe in an intermediate growth regime, and aOE (c) 112 > in a higher growth rate regime. In-depth analysis of the atomic configuration of a solid-liquid interface revealed that the growth texture is influenced by the kinetics of atomic attachment to the solid-liquid interface, which is intimately related to a planar packing fraction and an atomic stacking sequence of the interfacial plane. The mechanism proposed in this article is novel and will be useful in addressing the orientation selection mechanism of topologically closed packed intermetallic systems. The samples grown at a higher growth rate exhibit larger magnetostriction (lambda) and d lambda/dH owing to the absence of pro-peritectic (Tb,Dy)Fe-3 and formation of aOE (c) 112 > texture, which lies closer to the easy magnetization direction (EMD).

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Since streaming data keeps coming continuously as an ordered sequence, massive amounts of data is created. A big challenge in handling data streams is the limitation of time and space. Prototype selection on streaming data requires the prototypes to be updated in an incremental manner as new data comes in. We propose an incremental algorithm for prototype selection. This algorithm can also be used to handle very large datasets. Results have been presented on a number of large datasets and our method is compared to an existing algorithm for streaming data. Our algorithm saves time and the prototypes selected gives good classification accuracy.