955 resultados para Modular programming.


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We present the circuit board integration of a self-healing mechanism to repair open faults. The electric field driven mechanism physically restores fractured interconnects in electronic circuits and has the ability to solve mazes. The repair is performed by conductive particles dispersed in an insulating fluid. We demonstrate the integration of the healing module onto printed circuit boards and the ability of maze solving. We model and perform experiments on the influence of the geometry of conductive particles as well as the terminal impedances of the route on the healing efficiency. The typical heal rate is 10 mu m/s with healed route having mean resistance of 8 k Omega across a 200 micron gap and depending on the materials and concentrations used. (C) 2015 AIP Publishing LLC.

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Consider N points in R-d and M local coordinate systems that are related through unknown rigid transforms. For each point, we are given (possibly noisy) measurements of its local coordinates in some of the coordinate systems. Alternatively, for each coordinate system, we observe the coordinates of a subset of the points. The problem of estimating the global coordinates of the N points (up to a rigid transform) from such measurements comes up in distributed approaches to molecular conformation and sensor network localization, and also in computer vision and graphics. The least-squares formulation of this problem, although nonconvex, has a well-known closed-form solution when M = 2 (based on the singular value decomposition (SVD)). However, no closed-form solution is known for M >= 3. In this paper, we demonstrate how the least-squares formulation can be relaxed into a convex program, namely, a semidefinite program (SDP). By setting up connections between the uniqueness of this SDP and results from rigidity theory, we prove conditions for exact and stable recovery for the SDP relaxation. In particular, we prove that the SDP relaxation can guarantee recovery under more adversarial conditions compared to earlier proposed spectral relaxations, and we derive error bounds for the registration error incurred by the SDP relaxation. We also present results of numerical experiments on simulated data to confirm the theoretical findings. We empirically demonstrate that (a) unlike the spectral relaxation, the relaxation gap is mostly zero for the SDP (i.e., we are able to solve the original nonconvex least-squares problem) up to a certain noise threshold, and (b) the SDP performs significantly better than spectral and manifold-optimization methods, particularly at large noise levels.

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This paper focuses on understanding the seismic response of geosynthetic reinforced retaining walls through shaking table tests on models of modular block and rigid faced reinforced retaining walls. Reduced-scale models of retaining walls reinforced with geogrid layers were constructed in a laminar box mounted on a uniaxial shaking table and subjected to various levels of sinusoidal base shaking. Models were instrumented with ultrasonic displacement sensors, earth pressure sensors and accelerometers. Effects of backfill density, number of reinforcement layers and reinforcement type on the performance of rigid faced and modular block walls were studied through different series of model tests. Performances of the walls were assessed in terms of face deformations, crest settlement and acceleration amplification at different elevations and compared. Modular block walls performed better than the rigid faced walls for the same level of base shaking because of the additional support derived by stacking the blocks with an offset. Type and quantity of reinforcement has significant effect on the seismic performance of both the types of walls. Displacements are more sensitive to relative density of the backfill and decrease with increasing relative density, the effect being more pronounced in case of unreinforced walls compared to the reinforced ones. Acceleration amplifications are not affected by the wall facing and inclusion of reinforcement. (C) 2015 Elsevier Ltd. All rights reserved.

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We prove a sub-convex estimate for the sup-norm of L-2-normalized holomorphic modular forms of weight k on the upper half plane, with respect to the unit group of a quaternion division algebra over Q. More precisely we show that when the L-2 norm of an eigenfunction f is one, parallel to f parallel to(infinity) <<(epsilon) k(1/2-1/33+epsilon) for any epsilon > 0 and for all k sufficiently large.

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Post-transcriptional modification of viral mRNA is essential for the translation of viral proteins by cellular translation machinery. Due to the cytoplasmic replication of Paramyxoviruses, the viral-encoded RNA-dependent RNA polymerase (RdRP) is thought to possess all activities required for mRNA capping and methylation. In the present work, using partially purified recombinant RNA polymerase complex of rinderpest virus expressed in insect cells, we demonstrate the in vitro methylation of capped mRNA. Further, we show that a recombinant C-terminal fragment (1717-2183 aa) of L protein is capable of methylating capped mRNA, suggesting that the various post-transcriptional activities of the L protein are located in independently folding domains.

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Modular chiral I3-organochalcogeno amines, ArYCH2CH(R)NH2 (4a-4g) where R = Me, Bz, Ph; and ArY = PhS, BzSe and 4-MeOC6H4Te respectively have been synthesized and characterized. Compounds 4a-4g were synthesized (Method II) from chiral aminoalkyl 13-methanesulfonate hydrochlorides, MsOCH2CH(R)NH3+ center dot Cl- (2a-2c) through nucleophilic displacement of MsO- with organochalcogenolate (ArY-). In another attempt (Method I) chiral beta-organotelluro amines (4a-4c) were prepared by deprotection of chiral N-boc I3-organotelluro amides, 4-MeOC6H4TeCH2CH(R)NH-Boc (3a-3c), which in turn, 13,-,1 were made from chiral N-boc 13-methanesulfonate amides (la-lc) and ArTeNa. 1H, and FTIR spectra of all the compounds (3a-3c and 4a-4g) were characteristic. The composition of 3a-3c was determined by elemental analysis. The a]TD values of 3b-3c and 4a-4g were determined. The single crystal structures of (S)-2b and (R)-2c were determined by X-Ray diffraction studies. Both (S)-2b and (R)2c were crystallized in orthorhombic system and the Flack parameter x was found 0.08(12) and 0.00(2) respectively. The crystal of (S)-2b contain two asymmetric units with gauche (A) and staggered (B) conformations. There are NH Cl-, NH-O and CH-O intra and intermolecular secondary interactions in (S)-2b and (R)-2c resulting in supramolecular structures. (C) 2015 Elsevier By. All rights reserved.

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Let Gamma subset of SL2(Z) be a principal congruence subgroup. For each sigma is an element of SL2(Z), we introduce the collection A(sigma)(Gamma) of modular Hecke operators twisted by sigma. Then, A(sigma)(Gamma) is a right A(Gamma)-module, where A(Gamma) is the modular Hecke algebra introduced by Connes and Moscovici. Using the action of a Hopf algebra h(0) on A(sigma)(Gamma), we define reduced Rankin-Cohen brackets on A(sigma)(Gamma). Moreover A(sigma)(Gamma) carries an action of H 1, where H 1 is the Hopf algebra of foliations of codimension 1. Finally, we consider operators between the levels A(sigma)(Gamma), sigma is an element of SL2(Z). We show that the action of these operators can be expressed in terms of a Hopf algebra h(Z).

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In this paper the soft lunar landing with minimum fuel expenditure is formulated as a nonlinear optimal guidance problem. The realization of pinpoint soft landing with terminal velocity and position constraints is achieved using Model Predictive Static Programming (MPSP). The high accuracy of the terminal conditions is ensured as the formulation of the MPSP inherently poses final conditions as a set of hard constraints. The computational efficiency and fast convergence make the MPSP preferable for fixed final time onboard optimal guidance algorithm. It has also been observed that the minimum fuel requirement strongly depends on the choice of the final time (a critical point that is not given due importance in many literature). Hence, to optimally select the final time, a neural network is used to learn the mapping between various initial conditions in the domain of interest and the corresponding optimal flight time. To generate the training data set, the optimal final time is computed offline using a gradient based optimization technique. The effectiveness of the proposed method is demonstrated with rigorous simulation results.

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In this paper, we present a survey of the recent results on the characterization of the cuspidality of classical modular forms on various groups by a suitable growth of their Fourier coefficients.