Ancilla-assisted measurements on quantum ensembles: general protocols and applications in NMR quantum information processing

Quantum ensembles form easily accessible architectures for studying various phenomena in quantum physics, quantum information science and spectroscopy. Here we review some recent protocols for measurements in quantum ensembles by utilizing ancillary systems. We also illustrate these protocols experimentally via nuclear magnetic resonance techniques. In particular, we shall review noninvasive measurements, extracting expectation values of various operators, characterizations of quantum states and quantum processes, and finally quantum noise engineering.

Macroporous three-dimensional graphene oxide foams for dye adsorption and antibacterial applications

Several reports illustrate the wide range applicability of graphene oxide (GO) in water remediation. However, a few layers of graphene oxide tend to aggregate under saline conditions thereby reducing its activity. The effects of aggregation can be minimized by having a random arrangement of GO layers in a three dimensional architecture. The current study emphasizes the potential benefits of highly porous, ultralight graphene oxide foams in environmental applications. These foams were prepared by a facile and cost effective lyophilization technique. The 3D architecture allowed the direct use of these foams in the removal of aqueous pollutants without any pretreatment such as ultrasonication. Due to its macroporous nature, the foams exhibited excellent adsorption abilities towards carcinogenic dyes such as rhodamine B (RB), malachite green (MG) and acriflavine (AF) with respective sorption capacities of 446, 321 and 228 mg g(-1) of foam. These foams were also further investigated for antibacterial activities against E. coli bacteria in aqueous and nutrient growth media. The random arrangement of GO layers in the porous foam architecture allowed it to exhibit excellent antibacterial activity even under physiological conditions by following the classical wrapping-perturbation mechanism. These results demonstrate the vast scope of GO foam in water remediation for both dye removal and antibacterial activity.

Red-emitting LaOF:Eu3+ phosphors: Synthesis, structure and their Judd-Ofelt analysis for LED applications

In the present study, we have synthesized a series of La1-xEuxOF (0.01 <= x <= 0.09) phosphors by the conventional solid-state reaction route at relatively low temperature (500 degrees C) and shorter duration of 2 h. The compounds were crystallized in the rhombohedral structure with the space group R-3m (No. 166). Upon UV excitation (254 nm), the photoluminescence spectra exhibit characteristic luminescence D-5(0) -> F-7(J) (J= 1, 2, 3, and 4) intra-4f shell Eu3+ ion transitions. An intense red emission peak at 610 nm was observed due to electric dipole (D-5(0) -> F-7(2)) transition. Judd-Ofelt theory was employed to evaluate various radiative parameters such as radiative emission rates, lifetime, branching and asymmetry ratios. CIE color coordinates confirmed the red emission of the phosphors. The luminescent results reveal that LaOF:Eu3+ phosphor can be used as potential candidate for developing red component in white LED applications. (C) 2015 Elsevier Ltd. All rights reserved.

Selection of Optimal Time-to-go in Generalized Vector Explicit Guidance

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).

Inverse Polynomial Based Explicit Guidance for Lunar Soft Landing During Powered Braking

In this paper an explicit guidance law for the powered descent phase of the soft lunar landing is presented. The descent trajectory, expressed in polynomial form is fixed based on the boundary conditions imposed by the precise soft landing mission. Adapting an inverse model based approach, the guidance command is computed from the known spacecraft trajectory. The guidance formulation ensures the vertical orientation of the spacecraft during touchdown. Also a closed form relation for the final flight time is proposed. The final time is expressed as a function of initial position and velocity of the spacecraft ( at the start of descent) and also depends on the desired landing site. To ensure the fuel minimum descent the proposed explicit method is extended to optimal guidance formulation. The effectiveness of the proposed guidance laws are demonstrated with simulation results.

Fuel-optimal G-MPSP Guidance for Powered Descent Phase of Soft Lunar Landing

A fuel optimal nonlinear sub-optimal guidance scheme is presented in this paper for soft landing of a lunar craft during the powered descent phase. The recently developed Generalized Model Predictive Static Programming (G-MPSP) is used to compute the required magnitude and angle of the thrust vector. Both terminal position and velocity vector are imposed as hard constraints, which ensures high position accuracy and facilitates initiation of vertical descent at the end of the powered descent phase. A key feature of the G-MPSP algorithm is that it converts the nonlinear dynamic programming problem into a low-dimensional static optimization problem (of the same dimension as the output vector). The control history update is done in closed form after computing a time-varying weighting matrix through a backward integration process. This feature makes the algorithm computationally efficient, which makes it suitable for on-board applications. The effectiveness of the proposed guidance algorithm is demonstrated through promising simulation results.

Conceptual design of three-dimensional scaffolds of powder-based materials for bone tissue engineering applications

Purpose - The purpose of this paper is to investigate the possibility to construct tissue-engineered bone repair scaffolds with pore size distributions using rapid prototyping techniques. Design/methodology/approach - The fabrication of porous scaffolds with complex porous architectures represents a major challenge in tissue engineering and the design aspects to mimic complex pore shape as well as spatial distribution of pore sizes of natural hard tissue remain unexplored. In this context, this work aims to evaluate the three-dimensional printing process to study its potential for scaffold fabrication as well as some innovative design of homogeneously porous or gradient porous scaffolds is described and such design has wider implication in the field of bone tissue engineering. Findings - The present work discusses biomedically relevant various design strategies with spatial/radial gradient in pore sizes as well as with different pore sizes and with different pore geometries. Originality/value - One of the important implications of the proposed novel design scheme would be the development of porous bioactive/biodegradable composites with gradient pore size, porosity, composition and with spatially distributed biochemical stimuli so that stem cells loaded into scaffolds would develop into complex tissues such as those at the bone-cartilage interface.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

A coupled discriminative dictionary and transformation learning approach with applications to cross domain matching

Cross domain and cross-modal matching has many applications in the field of computer vision and pattern recognition. A few examples are heterogeneous face recognition, cross view action recognition, etc. This is a very challenging task since the data in two domains can differ significantly. In this work, we propose a coupled dictionary and transformation learning approach that models the relationship between the data in both domains. The approach learns a pair of transformation matrices that map the data in the two domains in such a manner that they share common sparse representations with respect to their own dictionaries in the transformed space. The dictionaries for the two domains are learnt in a coupled manner with an additional discriminative term to ensure improved recognition performance. The dictionaries and the transformation matrices are jointly updated in an iterative manner. The applicability of the proposed approach is illustrated by evaluating its performance on different challenging tasks: face recognition across pose, illumination and resolution, heterogeneous face recognition and cross view action recognition. Extensive experiments on five datasets namely, CMU-PIE, Multi-PIE, ChokePoint, HFB and IXMAS datasets and comparisons with several state-of-the-art approaches show the effectiveness of the proposed approach. (C) 2015 Elsevier B.V. All rights reserved.

Mitigating instability by actuating the swirler in a combustor

Thermoacoustic instability in a lean premixed combustor is a major impediment towards reliable operation of gas turbine engines for both aerospace and land based applications. In this communication, we investigate the following concept: in a laboratory combustor, could the otherwise static swirler be actuated to a rotary motion, such that the higher intensity turbulence and higher swirl number generated in the flame stabilization region might alter the flame position, structure and thereby assist in mitigating thermoacoustic instabilities? Results obtained using microphone and high speed imaging, show prominent reductions in the amplitudes of the first mode of the thermoacoustically unstable flame, with increased rotation rate of the swirler. (C) 2015 The Combustion Institute. Published by Elsevier Inc. All rights reserved.

Solution processed Cu2SnS3 thin films for visible and infrared photodetector applications

The Cu2SnS3 thin films were deposited using an economic, solution processible, spin coating technique. The films were found to possess a tetragonal crystal structure using X-ray diffraction. The film morphology and the particle size were determined using scanning electron microscopy. The various planes in the crystal were observed using transmission electron microscopy. The optimum band gap of 1.23 eV and a high absorption coefficient of 104 cm-1 corroborate its application as a photoactive material. The visible and infrared (IR) photo response was studied for various illumination intensities. The current increased by one order from a dark current of 0.31 mu A to a current of 1.78 mu A at 1.05 suns and 8.7 mu A under 477.7 mW/cm(2) IR illumination intensity, at 3 V applied bias. The responsivity, sensitivity, external quantum efficiency and specific detectivity were found to be 10.93 mA/W, 5.74, 2.47% and 3.47 x 10(10) Jones respectively at 1.05 suns and 16.32 mA/W, 27.16, 2.53% and 5.10 x 10(10) Jones respectively at 477.7 mW/cm(2) IR illumination. The transient photoresponse was measured both for visible and IR illuminations. (C) 2016 Author(s).

Damage assessment of composite plate structures with material and measurement uncertainty

Composite materials are very useful in structural engineering particularly in weight sensitive applications. Two different test models of the same structure made from composite materials can display very different dynamic behavior due to large uncertainties associated with composite material properties. Also, composite structures can suffer from pre-existing imperfections like delaminations, voids or cracks during fabrication. In this paper, we show that modeling and material uncertainties in composite structures can cause considerable problein in damage assessment. A recently developed C-0 shear deformable locking free refined composite plate element is employed in the numerical simulations to alleviate modeling uncertainty. A qualitative estimate of the impact of modeling uncertainty on the damage detection problem is made. A robust Fuzzy Logic System (FLS) with sliding window defuzzifier is used for delamination damage detection in composite plate type structures. The FLS is designed using variations in modal frequencies due to randomness in material properties. Probabilistic analysis is performed using Monte Carlo Simulation (MCS) on a composite plate finite element model. It is demonstrated that the FLS shows excellent robustness in delamination detection at very high levels of randomness in input data. (C) 2016 Elsevier Ltd. All rights reserved.

A Novel Approach for Multispectral Satellite Image Classification Based on the Bat Algorithm

Among the multiple advantages and applications of remote sensing, one of the most important uses is to solve the problem of crop classification, i.e., differentiating between various crop types. Satellite images are a reliable source for investigating the temporal changes in crop cultivated areas. In this letter, we propose a novel bat algorithm (BA)-based clustering approach for solving crop type classification problems using a multispectral satellite image. The proposed partitional clustering algorithm is used to extract information in the form of optimal cluster centers from training samples. The extracted cluster centers are then validated on test samples. A real-time multispectral satellite image and one benchmark data set from the University of California, Irvine (UCI) repository are used to demonstrate the robustness of the proposed algorithm. The performance of the BA is compared with two other nature-inspired metaheuristic techniques, namely, genetic algorithm and particle swarm optimization. The performance is also compared with the existing hybrid approach such as the BA with K-means. From the results obtained, it can be concluded that the BA can be successfully applied to solve crop type classification problems.

Na2M2(SO4)(3) (M = Fe, Mn, Co and Ni): towards high-voltage sodium battery applications

Sodium-ion-based batteries have evolved as excellent alternatives to their lithium-ion-based counterparts due to the abundance, uniform geographical distribution and low price of Na resources. In the pursuit of sodium chemistry, recently the alluaudite framework Na2M2(SO4)(3) has been unveiled as a high-voltage sodium insertion system. In this context, the framework of density functional theory has been applied to systematically investigate the crystal structure evolution, density of states and charge transfer with sodium ions insertion, and the corresponding average redox potential, for Na2M2(SO4)(3) (M = Fe, Mn, Co and Ni). It is shown that full removal of sodium atoms from the Fe-based device is not a favorable process due to the 8% volume shrinkage. The imaginary frequencies obtained in the phonon dispersion also reflect this instability and the possible phase transition. This high volume change has not been observed in the cases of the Co- and Ni-based compounds. This is because the redox reaction assumes a different mechanism for each of the compounds investigated. For the polyanion with Fe, the removal of sodium ions induces a charge reorganization at the Fe centers. For the Mn case, the redox process induces a charge reorganization of the Mn centers with a small participation of the oxygen atoms. The Co and Ni compounds present a distinct trend with the redox reaction occurring with a strong participation of the oxygen sublattice, resulting in a very small volume change upon desodiation. Moreover, the average deintercalation potential for each of the compounds has been computed. The implications of our findings have been discussed both from the scientific perspective and in terms of technological aspects.