Optimal Forwarding in Delay-Tolerant Networks With Multiple Destinations

We study the tradeoff between delivery delay and energy consumption in a delay-tolerant network in which a message (or a file) has to be delivered to each of several destinations by epidemic relaying. In addition to the destinations, there are several other nodes in the network that can assist in relaying the message. We first assume that, at every instant, all the nodes know the number of relays carrying the message and the number of destinations that have received the message. We formulate the problem as a controlled continuous-time Markov chain and derive the optimal closed-loop control (i.e., forwarding policy). However, in practice, the intermittent connectivity in the network implies that the nodes may not have the required perfect knowledge of the system state. To address this issue, we obtain an ordinary differential equation (ODE) (i.e., a deterministic fluid) approximation for the optimally controlled Markov chain. This fluid approximation also yields an asymptotically optimal open-loop policy. Finally, we evaluate the performance of the deterministic policy over finite networks. Numerical results show that this policy performs close to the optimal closed-loop policy.

Self-assembly of discrete metallamacrocycles employing half-sandwich octahedral diruthenium(II) building units and imidazole-based ligands

Equimolar combination of a series of binuclear half-sandwich p-cymene ruthenium(II) building units Ru-2(mu-eta(4)-C2O4)(MeOH)(2)(eta(6)-p-cymene)(2)](OTf)(2) 1a](OTf)(2), Ru-2(mu-eta(4)-N,N'-diphenyloxamidato)( MeOH)(2)(eta(6)-p-cymene)(2)](OTf)(2) 1b](OTf)(2) and Ru-2(mu-eta(4)-C6H2O4)(MeOH)(2)(eta(6)-p-cymene)(2)](OTf)(2) 1c](OTf)(2) separately with imidazole-based ditopic ligands (L-1-L-2) in methanol yielded a series of tetranuclear metallamacrocycles 2-7](OTf)(4), respectively L-1 = 1,4-bis(imidazole-1-yl)benzene; L-2 = 4,4'-bis(imidazole-1-yl)biphenyl; OTf- = O3SCF3-]. Similarly, the reaction of Ru-2(mu-eta(4)-C2O4)(MeOH)(2)(eta(6)-p-cymene)2](OTf)(2) 1a](OTf)(2) with a triazine-based tritopic ligand 1,3,5-tris(imidazole-1-yl) triazine (L3) in 3: 2 M ratio afforded an unexpected tetranuclear macrocycle 8](OTf)(4) instead of an expected trigonal prismatic cage 8a](OTf)(6). All the self-assembled macrocycles 2-8](OTf)(4) were isolated in moderate to high yields and were fully characterized by multinuclear H-1, F-19] NMR, IR and electrospray ionization mass spectrometry (ESI-MS). In addition, X-ray diffraction study on the single crystals of 3](OTf)(4) and 8](OTf)(4) also indicated the formation 2 + 2] self-assembled macrocycles. Despite the possibility of formation of different conformational isomeric macrocycles (syn-and anti) and polymeric product due to free rotation of ligand sites of imidazole linkers, the selective formation of single conformational isomer (anti) as the only product is quite interesting. Furthermore, the photo-and electrochemical properties of these assemblies have been studied using UV/Vis absorption and cyclic voltammetry analysis. (c) 2013 Elsevier B.V. All rights reserved.

Bivariate frequency analysis of floods using a diffusion based kernel density estimator

Recent focus of flood frequency analysis (FFA) studies has been on development of methods to model joint distributions of variables such as peak flow, volume, and duration that characterize a flood event, as comprehensive knowledge of flood event is often necessary in hydrological applications. Diffusion process based adaptive kernel (D-kernel) is suggested in this paper for this purpose. It is data driven, flexible and unlike most kernel density estimators, always yields a bona fide probability density function. It overcomes shortcomings associated with the use of conventional kernel density estimators in FFA, such as boundary leakage problem and normal reference rule. The potential of the D-kernel is demonstrated by application to synthetic samples of various sizes drawn from known unimodal and bimodal populations, and five typical peak flow records from different parts of the world. It is shown to be effective when compared to conventional Gaussian kernel and the best of seven commonly used copulas (Gumbel-Hougaard, Frank, Clayton, Joe, Normal, Plackett, and Student's T) in estimating joint distribution of peak flow characteristics and extrapolating beyond historical maxima. Selection of optimum number of bins is found to be critical in modeling with D-kernel.

Novel 2,6-bis(4-methoxyphenyl)-1-methylpiperidin-4-one oxime esters: synthesis and a new insight into their antioxidant and antimicrobial potential

A simple and efficient protocol for the synthesis of novel 2,6-bis(4-methoxyphenyl)-1-methylpiperidin-4-one oxime esters 4(a-q) is described. Initially, p-anisaldehyde 1 was condensed (Mannich reaction) with acetone and ammonium acetate trihydrate afforded 2,6-bis(4-methoxyphenyl)piperidin-4-one 2. Then, methylation followed by oximation with hydroxylamine hydrochloride (NH(2)OHa (TM) HCl) furnished a key scaffold 4. Further, to explore the enhanced biological properties of the piperidin-4-one core i.e. the key scaffold 4 was conjugated with substituted benzoyl chlorides in the presence of anhydrous K2CO3 as base to obtain novel 2,6-bis(4-methoxyphenyl)-1-methylpiperidin-4-one oxime esters 4(a-q) in excellent yields. The newly synthesized compounds were characterized by elemental analysis, IR, H-1 NMR, C-13 NMR and mass spectroscopic techniques, and screened for their in vitro antioxidant and antimicrobial activities. Most of the compounds exerted positive efficacy towards the biological assays performed. Among the synthesized analogues, compounds 4l and 4m exhibited promising antioxidant activity and on the other hand compounds 4b and 4d manifested persuasive antibacterial activity, whereas compound 4b displayed stupendous antifungal activity against A. flavus strain.

Photocurrent spectroscopic studies of diketopyrrolopyrrole-based statistical copolymers

Diketopyrrolopyrrole (DPP) containing copolymers have gained a lot of interest in organic optoelectronics with great potential in organic photovoltaics. In this work, DPP based statistical copolymers, with slightly different bandgap energies and a varying fraction of donor-acceptor ratio are investigated using monochromatic photocurrent spectroscopy and Fourier-transform photocurrent spectroscopy (FTPS). The statistical copolymer with a lower DPP fraction, when blended with a fullerene derivative, shows the signature of an inter charge transfer complex state in photocurrent spectroscopy. Furthermore, the absorption spectrum of the blended sample with a lower DPP fraction is seen to change as a function of an external bias, qualitatively similar to the quantum confined Stark effect, from where we estimate the exciton binding energy. The statistical copolymer with a higher DPP fraction shows no signal of the inter charge transfer states and yields a higher external quantum efficiency in a photovoltaic structure. In order to gain insight into the origin of the observed charge transfer transitions, we present theoretical studies using density-functional theory and time-dependent density-functional theory for the two pristine DPP based statistical monomers.

Photocurrent spectroscopic studies of diketopyrrolopyrrole-based statistical copolymers

Diketopyrrolopyrrole (DPP) containing copolymers have gained a lot of interest in organic optoelectronics with great potential in organic photovoltaics. In this work, DPP based statistical copolymers, with slightly different bandgap energies and a varying fraction of donor-acceptor ratio are investigated using monochromatic photocurrent spectroscopy and Fourier-transform photocurrent spectroscopy (FTPS). The statistical copolymer with a lower DPP fraction, when blended with a fullerene derivative, shows the signature of an inter charge transfer complex state in photocurrent spectroscopy. Furthermore, the absorption spectrum of the blended sample with a lower DPP fraction is seen to change as a function of an external bias, qualitatively similar to the quantum confined Stark effect, from where we estimate the exciton binding energy. The statistical copolymer with a higher DPP fraction shows no signal of the inter charge transfer states and yields a higher external quantum efficiency in a photovoltaic structure. In order to gain insight into the origin of the observed charge transfer transitions, we present theoretical studies using density-functional theory and time-dependent density-functional theory for the two pristine DPP based statistical monomers.

Simulation of inhomogeneous distributions of ultracold atoms in an optical lattice via a massively parallel implementation of nonequilibrium strong-coupling perturbation theory

We present a nonequilibrium strong-coupling approach to inhomogeneous systems of ultracold atoms in optical lattices. We demonstrate its application to the Mott-insulating phase of a two-dimensional Fermi-Hubbard model in the presence of a trap potential. Since the theory is formulated self-consistently, the numerical implementation relies on a massively parallel evaluation of the self-energy and the Green's function at each lattice site, employing thousands of CPUs. While the computation of the self-energy is straightforward to parallelize, the evaluation of the Green's function requires the inversion of a large sparse 10(d) x 10(d) matrix, with d > 6. As a crucial ingredient, our solution heavily relies on the smallness of the hopping as compared to the interaction strength and yields a widely scalable realization of a rapidly converging iterative algorithm which evaluates all elements of the Green's function. Results are validated by comparing with the homogeneous case via the local-density approximation. These calculations also show that the local-density approximation is valid in nonequilibrium setups without mass transport.

Co-registration of speech production datasets from electromagnetic articulography and real-time magnetic resonance imaging

This paper describes a spatio-temporal registration approach for speech articulation data obtained from electromagnetic articulography (EMA) and real-time Magnetic Resonance Imaging (rtMRI). This is motivated by the potential for combining the complementary advantages of both types of data. The registration method is validated on EMA and rtMRI datasets obtained at different times, but using the same stimuli. The aligned corpus offers the advantages of high temporal resolution (from EMA) and a complete mid-sagittal view (from rtMRI). The co-registration also yields optimum placement of EMA sensors as articulatory landmarks on the magnetic resonance images, thus providing richer spatio-temporal information about articulatory dynamics. (C) 2014 Acoustical Society of America

Efficiency limitations in a low band-gap diketopyrrolopyrrole-based polymer solar cell

We report the performance and photophysics of a low band-gap diketopyrrolopyrrole-based copolymer used in bulk heterojunction devices in combination with PC71BM. We show that the short lifetime of photogenerated excitons in the polymer constitutes an obstacle towards device efficiency by limiting the diffusion range of the exciton to the donor-acceptor heterojunction. We employ ultrafast transient-probe and fluorescence spectroscopy techniques to examine the excited state loss channels inside the devices. We use the high boiling point solvent additive 1,8-diiodooctane (DIO) to study the photoexcited state losses in different blend morphologies. The solvent additive acts as a compatibiliser between the donor and the acceptor material and leads to smaller domain sizes, higher charge formation yields and increased device efficiency.

Automatic Data Allocation and Buffer Management for Multi-GPU Machines

Multi-GPU machines are being increasingly used in high-performance computing. Each GPU in such a machine has its own memory and does not share the address space either with the host CPU or other GPUs. Hence, applications utilizing multiple GPUs have to manually allocate and manage data on each GPU. Existing works that propose to automate data allocations for GPUs have limitations and inefficiencies in terms of allocation sizes, exploiting reuse, transfer costs, and scalability. We propose a scalable and fully automatic data allocation and buffer management scheme for affine loop nests on multi-GPU machines. We call it the Bounding-Box-based Memory Manager (BBMM). BBMM can perform at runtime, during standard set operations like union, intersection, and difference, finding subset and superset relations on hyperrectangular regions of array data (bounding boxes). It uses these operations along with some compiler assistance to identify, allocate, and manage data required by applications in terms of disjoint bounding boxes. This allows it to (1) allocate exactly or nearly as much data as is required by computations running on each GPU, (2) efficiently track buffer allocations and hence maximize data reuse across tiles and minimize data transfer overhead, and (3) and as a result, maximize utilization of the combined memory on multi-GPU machines. BBMM can work with any choice of parallelizing transformations, computation placement, and scheduling schemes, whether static or dynamic. Experiments run on a four-GPU machine with various scientific programs showed that BBMM reduces data allocations on each GPU by up to 75% compared to current allocation schemes, yields performance of at least 88% of manually written code, and allows excellent weak scaling.

Performance evaluation of typical approximation algorithms for nonconvex l(p)-minimization in diffuse optical tomography

The sparse estimation methods that utilize the l(p)-norm, with p being between 0 and 1, have shown better utility in providing optimal solutions to the inverse problem in diffuse optical tomography. These l(p)-norm-based regularizations make the optimization function nonconvex, and algorithms that implement l(p)-norm minimization utilize approximations to the original l(p)-norm function. In this work, three such typical methods for implementing the l(p)-norm were considered, namely, iteratively reweighted l(1)-minimization (IRL1), iteratively reweighted least squares (IRLS), and the iteratively thresholding method (ITM). These methods were deployed for performing diffuse optical tomographic image reconstruction, and a systematic comparison with the help of three numerical and gelatin phantom cases was executed. The results indicate that these three methods in the implementation of l(p)-minimization yields similar results, with IRL1 fairing marginally in cases considered here in terms of shape recovery and quantitative accuracy of the reconstructed diffuse optical tomographic images. (C) 2014 Optical Society of America

Model-Resolution-Based Basis Pursuit Deconvolution Improves Diffuse Optical Tomographic Imaging

The image reconstruction problem encountered in diffuse optical tomographic imaging is ill-posed in nature, necessitating the usage of regularization to result in stable solutions. This regularization also results in loss of resolution in the reconstructed images. A frame work, that is attributed by model-resolution, to improve the reconstructed image characteristics using the basis pursuit deconvolution method is proposed here. The proposed method performs this deconvolution as an additional step in the image reconstruction scheme. It is shown, both in numerical and experimental gelatin phantom cases, that the proposed method yields better recovery of the target shapes compared to traditional method, without the loss of quantitativeness of the results.

Azide/thiocyanate incorporated cobalt(III)-Schiff base complexes: Characterizations and catalytic activity in aerobic epoxidation of olefins

Reaction of cobalt(II) perchlorate hexahydrate with a potentially tetradentate Schiff base ligand, HL (2-methoxy-6-(2-diethylaminoethylimino)methyl]phenol) in presence of sodium azide and sodium thiocyanate yields two complexes Co( L)( HL)(N-3)]center dot ClO4 ( 1) and Co( L)( HL)(NCS)] center dot ClO4 ( 2); both being characterized by different physicochemical methods. Crystal structure of 1 was determined by single crystal X-ray diffraction while that of 2 was reported earlier. In 1, the central cobalt(III) adopts slightly distorted octahedral geometry with same donor set to that of 2. Catalytic efficacy of the complexes towards epoxidation of different alkenes under aerobic condition were investigated in homogeneous medium which reveals that 1 is better catalyst than 2 with respect to alkene oxidation, reflected from the turn over frequencies (TOF) measured at an optimum temperature of 60 degrees C in acetonitrile. (C) 2014 Published by Elsevier B.V.

Quantum-Confined ZnO Nanoshell Photoanodes for Mesoscopic Solar Cells

We present a photoanode for dye-sensitized solar cell (DSC) based on ZnO nanoshell deposited by atomic layer deposition at 150 degrees C on a mesoporous insulating template. An ultrathin layer of ZnO between. 3 and 6 nm, which exhibits quantum confinement effect, is found to be sufficient to transport the photogenerated electrons to the external contacts and exhibits near-unity collection efficiency. A 6 nm ZnO nanoshell on a 2.5 mu m mesoporous nanoparticle Al2O3 template yields photovoltaic power conversion efficiency (PCE) of 4.2% in liquid DSC. Perovskite absorber (CH3NH3PbI3) based solid state solar cells made with similar ZnO nanostructures lead to a high PCE of 7%.

Effect of quantum nuclear motion on hydrogen bonding

This work considers how the properties of hydrogen bonded complexes, X-H center dot center dot center dot Y, are modified by the quantum motion of the shared proton. Using a simple two-diabatic state model Hamiltonian, the analysis of the symmetric case, where the donor (X) and acceptor (Y) have the same proton affinity, is carried out. For quantitative comparisons, a parametrization specific to the O-H center dot center dot center dot O complexes is used. The vibrational energy levels of the one-dimensional ground state adiabatic potential of the model are used to make quantitative comparisons with a vast body of condensed phase data, spanning a donor-acceptor separation (R) range of about 2.4-3.0 angstrom, i.e., from strong to weak hydrogen bonds. The position of the proton (which determines the X-H bond length) and its longitudinal vibrational frequency, along with the isotope effects in both are described quantitatively. An analysis of the secondary geometric isotope effect, using a simple extension of the two-state model, yields an improved agreement of the predicted variation with R of frequency isotope effects. The role of bending modes is also considered: their quantum effects compete with those of the stretching mode for weak to moderate H-bond strengths. In spite of the economy in the parametrization of the model used, it offers key insights into the defining features of H-bonds, and semi-quantitatively captures several trends. (C) 2014 AIP Publishing LLC.