Oscillatory exchange bias and training effects in nanocrystalline Pr0.5Ca0.5MnO3

We report on exchange bias effects in 10 nm particles of Pr0.5Ca0.5MnO3 which appear as a result of competing interactions between the ferromagnetic (FM)/anti-ferromagnetic (AFM) phases. The fascinating new observation is the demonstration of the temperature dependence of oscillatory exchange bias (OEB) and is tunable as a function of cooling field strength below the SG phase, may be attributable to the presence of charge/spin density wave (CDW/SDW) in the AFM core of PCMO10. The pronounced training effect is noticed at 5 K from the variation of the EB field as a function of number of field cycles (n) upon the field cooling (FC) process. For n > 1, power-law behavior describes the experimental data well; however, the breakdown of spin configuration model is noticed at n >= 1. Copyright 2012 Author(s). This article is distributed under a Creative Commons Attribution 3.0 Unported License. http://dx.doi.org/10.1063/1.3696033]

Synthesis and characterization of high molecular weight polyaniline for organic electronic applications

High molecular weight polyaniline (PANI) was synthesized by a combined procedure incorporating various synthesis methods. Temperature and open circuit potential of the reaction mixture were collected to monitor the reaction progress. The polymer is characterized by various techniques including gel permeation chromatography, dynamic light scattering, infrared spectroscopy, solid-state nuclear magnetic resonance, and differential scanning calorimetry for elucidating the molecular architecture obtained by this method. As-synthesized PANI was found to possess high molecular weight, reduced branching, reduced cross-linking, and to predominantly consist of linear polymer chains. This polymer was also found to be more stable in solution form. JV characteristics of as-synthesized PANI films indicate a high current density which is due to increased free pathways and less traps for the charge transport to occur in PANI films. POLYM. ENG. SCI., 2012. (C) 2012 Society of Plastics Engineers

Maximum weight independent sets in hole- and dart-free graphs

The Maximum Weight Independent Set (MWIS) problem on graphs with vertex weights asks for a set of pairwise nonadjacent vertices of maximum total weight. The complexity of the MWIS problem for hole-free graphs is unknown. In this paper, we first prove that the MWIS problem for (hole, dart, gem)-free graphs can be solved in O(n(3))-time. By using this result, we prove that the MWIS problem for (hole, dart)-free graphs can be solved in O(n(4))-time. Though the MWIS problem for (hole, dart, gem)-free graphs is used as a subroutine, we also give the best known time bound for the solvability of the MWIS problem in (hole, dart, gem)-free graphs. (C) 2012 Elsevier B.V. All rights reserved.

Power Controlled Reverse Channel Training Achieves an Infinite Diversity Order in a TDD-SIMO System with Perfect CSIR

In this letter, we analyze the Diversity Multiplexinggain Tradeoff (DMT) performance of a training-based reciprocal Single Input Multiple Output (SIMO) system. Assuming Channel State Information (CSI) is available at the Receiver (CSIR), we propose a channel-dependent power-controlled Reverse Channel Training (RCT) scheme that enables the transmitter to directly estimate the power control parameter to be used for the forwardlink data transmission. We show that, with an RCT power of (P) over bar (gamma), gamma > 0 and a forward data transmission power of (P) over bar, our proposed scheme achieves an infinite diversity order for 0 <= g(m) < L-c-L-B,L-tau/L-c min(gamma, 1) and r > 2, where g(m) is the multiplexing gain, L-c is the channel coherence time, L-B,L-tau is the RCT duration and r is the number of receive antennas. We also derive an upper bound on the outage probability and show that it goes to zero asymptotically as exp(-(P) over bar (E)), where E (sic) (gamma - g(m)L(c)/L-c-L-B,L-tau), at high (P) over bar. Thus, the proposed scheme achieves a significantly better DMT performance compared to the finite diversity order achieved by channel-agnostic, fixed-power RCT schemes.

Energy-efficient training for antenna selection in time-varying channels

Training for receive antenna selection (AS) differs from that for conventional multiple antenna systems because of the limited hardware usage inherent in AS. We analyze and optimize the performance of a novel energy-efficient training method tailored for receive AS. In it, the transmitter sends not only pilots that enable the selection process, but also an extra pilot that leads to accurate channel estimates for the selected antenna that actually receives data. For time-varying channels, we propose a novel antenna selection rule and prove that it minimizes the symbol error probability (SEP). We also derive closed-form expressions for the SEP of MPSK, and show that the considered training method is significantly more energy-efficient than the conventional AS training method.

A weight based context analysis system to provide a required UMM service

Ubiquitous Computing is an emerging paradigm which facilitates user to access preferred services, wherever they are, whenever they want, and the way they need, with zero administration. While moving from one place to another the user does not need to specify and configure their surrounding environment, the system initiates necessary adaptation by itself to cope up with the changing environment. In this paper we propose a system to provide context-aware ubiquitous multimedia services, without user’s intervention. We analyze the context of the user based on weights, identify the UMMS (Ubiquitous Multimedia Service) based on the collected context information and user profile, search for the optimal server to provide the required service, then adapts the service according to user’s local environment and preferences, etc. The experiment conducted several times with different context parameters, their weights and various preferences for a user. The results are quite encouraging.

A practical approach for cross-functional vehicle body weight optimization

The goal of optimization in vehicle design is often blurred by the myriads of requirements belonging to attributes that may not be quite related. If solutions are sought by optimizing attribute performance-related objectives separately starting with a common baseline design configuration as in a traditional design environment, it becomes an arduous task to integrate the potentially conflicting solutions into one satisfactory design. It may be thus more desirable to carry out a combined multi-disciplinary design optimization (MDO) with vehicle weight as an objective function and cross-functional attribute performance targets as constraints. For the particular case of vehicle body structure design, the initial design is likely to be arrived at taking into account styling, packaging and market-driven requirements. The problem with performing a combined cross-functional optimization is the time associated with running such CAE algorithms that can provide a single optimal solution for heterogeneous areas such as NVH and crash safety. In the present paper, a practical MDO methodology is suggested that can be applied to weight optimization of automotive body structures by specifying constraints on frequency and crash performance. Because of the reduced number of cases to be analyzed for crash safety in comparison with other MDO approaches, the present methodology can generate a single size-optimized solution without having to take recourse to empirical techniques such as response surface-based prediction of crash performance and associated successive response surface updating for convergence. An example of weight optimization of spaceframe-based BIW of an aluminum-intensive vehicle is given to illustrate the steps involved in the current optimization process.

Channel training signal design for reciprocal multiple antenna systems with beamforming

Fast and efficient channel estimation is key to achieving high data rate performance in mobile and vehicular communication systems, where the channel is fast time-varying. To this end, this work proposes and optimizes channel-dependent training schemes for reciprocal Multiple-Input Multiple-Output (MIMO) channels with beamforming (BF) at the transmitter and receiver. First, assuming that Channel State Information (CSI) is available at the receiver, a channel-dependent Reverse Channel Training (RCT) signal is proposed that enables efficient estimation of the BF vector at the transmitter with a minimum training duration of only one symbol. In contrast, conventional orthogonal training requires a minimum training duration equal to the number of receive antennas. A tight approximation to the capacity lower bound on the system is derived, which is used as a performance metric to optimize the parameters of the RCT. Next, assuming that CSI is available at the transmitter, a channel-dependent forward-link training signal is proposed and its power and duration are optimized with respect to an approximate capacity lower bound. Monte Carlo simulations illustrate the significant performance improvement offered by the proposed channel-dependent training schemes over the existing channel-agnostic orthogonal training schemes.

Hybrid organogels and aerogels from co-assembly of structurally different low molecular weight gelators

The blending of perfluorinated bile ester derivatives with the gelator 2,3-didecyloxyanthracene (DDOA) yields a new class of hybrid organo- and aerogels displaying a combination of optical and mechanical properties that differ from those of pure gels. Indeed, the nanofibers constituting the hybrid organogels emit polarized blue light and display dichroic near-UV absorption via the achiral DDOA molecules, thanks to their association with a chiral bile ester. Moreover, the thermal stability and the mechanical yield stress of the mixed organogels in DMSO are enhanced for blends of DDOA with the deoxycholic gelator (DC11) having a C-11 chain, as compared to the pure components' gels. When the chain length of the ester is increased to C-13 (DC13) a novel compound for aerogel formation directly in scCO(2) is obtained under the studied conditions. A mixture of this compound with DDOA is also able to gelate scCO(2) leading to novel composite aerogel materials. As revealed by SAXS measurements, the hybrid and the pure DDOA and DC13 aerogels display cell parameters that are very similar. These SAXS experiments suggest that crystallographic conditions are very favorable for the growth of hybrid molecular arrangements in which DDOA and DC13 units could be interchanged. Specific molecular interactions between two components are not always a pre-requisite condition for the formation of a hybrid nanostructured material in which the components mutually induce properties.

Synthesis and application of weight function for edge cracked semicircular disk (ECSD)

We analyze the utility of edge cracked semicircular disk (ECSD) for rapid assessment of fracture toughness using compressive loading. Continuing our earlier work on ECSD, a theoretical examination here leads to a novel way for synthesizing weight functions using two distinct form factors. The efficacy of ECSD mode-I weight function synthesized using displacement and form factor methods is demonstrated by comparing with finite element results. Theory of elasticity in conjunction with finite element method is utilized to analyze crack opening potency of ECSD under eccentric compression to explore newer configurations of ECSD for fracture testing.

Training for Antenna Selection in Time-Varying Channels: Optimal Selection, Energy Allocation, and Energy Efficiency Evaluation

Single receive antenna selection (AS) is a popular method for obtaining diversity benefits without the additional costs of multiple radio receiver chains. Since only one antenna receives at any time, the transmitter sends a pilot multiple times to enable the receiver to estimate the channel gains of its N antennas to the transmitter and select an antenna. In time-varying channels, the channel estimates of different antennas are outdated to different extents. We analyze the symbol error probability (SEP) in time-varying channels of the N-pilot and (N+1)-pilot AS training schemes. In the former, the transmitter sends one pilot for each receive antenna. In the latter, the transmitter sends one additional pilot that helps sample the channel fading process of the selected antenna twice. We present several new results about the SEP, optimal energy allocation across pilots and data, and optimal selection rule in time-varying channels for the two schemes. We show that due to the unique nature of AS, the (N+1)-pilot scheme, despite its longer training duration, is much more energy-efficient than the conventional N-pilot scheme. An extension to a practical scenario where all data symbols of a packet are received by the same antenna is also investigated.

Joint Antenna Selection and Frequency-Domain Scheduling in OFDMA Systems with Imperfect Estimates from Dual Pilot Training Scheme

Transmit antenna selection (AS) has been adopted in contemporary wideband wireless standards such as Long Term Evolution (LTE). We analyze a comprehensive new model for AS that captures several key features about its operation in wideband orthogonal frequency division multiple access (OFDMA) systems. These include the use of channel-aware frequency-domain scheduling (FDS) in conjunction with AS, the hardware constraint that a user must transmit using the same antenna over all its assigned subcarriers, and the scheduling constraint that the subcarriers assigned to a user must be contiguous. The model also captures the novel dual pilot training scheme that is used in LTE, in which a coarse system bandwidth-wide sounding reference signal is used to acquire relatively noisy channel state information (CSI) for AS and FDS, and a dense narrow-band demodulation reference signal is used to acquire accurate CSI for data demodulation. We analyze the symbol error probability when AS is done in conjunction with the channel-unaware, but fair, round-robin scheduling and with channel-aware greedy FDS. Our results quantify how effective joint AS-FDS is in dispersive environments, the interactions between the above features, and the ability of the user to lower SRS power with minimal performance degradation.

Power-Controlled Reverse Channel Training in a Multiuser TDD-MIMO Spatial Multiplexing System With CSIR

This paper considers the design of a power-controlled reverse channel training (RCT) scheme for spatial multiplexing (SM)-based data transmission along the dominant modes of the channel in a time-division duplex (TDD) multiple-input and multiple-output (MIMO) system, when channel knowledge is available at the receiver. A channel-dependent power-controlled RCT scheme is proposed, using which the transmitter estimates the beamforming (BF) vectors required for the forward-link SM data transmission. Tight approximate expressions for 1) the mean square error (MSE) in the estimate of the BF vectors, and 2) a capacity lower bound (CLB) for an SM system, are derived and used to optimize the parameters of the training sequence. Moreover, an extension of the channel-dependent training scheme and the data rate analysis to a multiuser scenario with M user terminals is presented. For the single-mode BF system, a closed-form expression for an upper bound on the average sum data rate is derived, which is shown to scale as ((L-c - L-B,L- tau)/L-c) log logM asymptotically in M, where L-c and L-B,L- tau are the channel coherence time and training duration, respectively. The significant performance gain offered by the proposed training sequence over the conventional constant-power orthogonal RCT sequence is demonstrated using Monte Carlo simulations.

Combinatorial effect of rolling and carbonaceous nanoparticles on the evolution of crystallographic texture and structural properties of ultra high molecular weight polyethylene

Ultra high molecular weight polyethylene (PE) is a structural polymer widely used in biomedical implants. The mechanical properties of PE can be improved either by controlled crystalline orientation (texture) or by the addition of reinforcing agents. However, the combinatorial effect has not received much attention. The objective of this study was to characterize the structure and mechanical properties of PE composites incorporating multiwall carbon nanotubes (MWCNT) and reduced graphene oxide (RGO) subjected to hot rolling. The wide angle X-ray diffraction studies revealed that mechanical deformation resulted in a mixture of orthorhombic and monoclinic crystals. Furthermore, the presence of nanoparticles resulted in lower crystallinity in PE with smaller crystallite size, more so in RGO than in MWCNT composites. Rolling strengthened the texture of both orthorhombic and the monoclinic phases in PE. Presence of RGO weakened the texture of both phases of PE after rolling whereas MWCNT only mildly weakened the texture. This resulted in a reduction in the elastic modulus of RGO composites whereas moduli of neat polymer and the MWCNT composite increased after rolling. This study provides new insight into the role of nanoparticles in texture evolution during polymer processing with implications for processing of structural polymer composites.

Belief propagation for minimum weight many-to-one matchings in the random complete graph

In a complete bipartite graph with vertex sets of cardinalities n and n', assign random weights from exponential distribution with mean 1, independently to each edge. We show that, as n -> infinity, with n' = n/alpha] for any fixed alpha > 1, the minimum weight of many-to-one matchings converges to a constant (depending on alpha). Many-to-one matching arises as an optimization step in an algorithm for genome sequencing and as a measure of distance between finite sets. We prove that a belief propagation (BP) algorithm converges asymptotically to the optimal solution. We use the objective method of Aldous to prove our results. We build on previous works on minimum weight matching and minimum weight edge cover problems to extend the objective method and to further the applicability of belief propagation to random combinatorial optimization problems.