An Inhibitor of Nonhomologous End-Joining Abrogates Double-Strand Break Repair and Impedes Cancer Progression

DNA Ligase IV is responsible for sealing of double-strand breaks (DSBs) during nonhomologous end-joining (NHEJ). Inhibiting Ligase IV could result in amassing of DSBs, thereby serving as a strategy toward treatment of cancer. Here, we identify a molecule, SCR7 that inhibits joining of DSBs in cell-free repair system. SCR7 blocks Ligase IV-mediated joining by interfering with its DNA binding but not that of T4 DNA Ligase or Ligase I. SCR7 inhibits NHEJ in a Ligase IV-dependent manner within cells, and activates the intrinsic apoptotic pathway. More importantly, SCR7 impedes tumor progression in mouse models and when coadministered with DSB-inducing therapeutic modalities enhances their sensitivity significantly. This inhibitor to target NHEJ offers a strategy toward the treatment of cancer and improvement of existing regimens.

Ballistic Studies on TiB2-Ti Functionally Graded Armor Ceramics

The objective of this paper is to discuss the results of the ballistic testing of spark plasma sintered TiB2-Ti based functionally graded materials (FGMs) with an aim to assess their performance in defeating small-calibre armor piercing projectiles. We studied the efficacy of FGM design and compared its ballistic properties with those of TiB2-based composites as well as other competing ceramic armors. The ballistic properties are critically analyzed in terms of depth of penetration, ballistic efficiency, fractographs of fractured surfaces as well as quantification of the shattered ceramic fragments. It was found that all the investigated ceramic compositions exhibit ballistic efficiency (eta) of 5.1 -5.9. We also found that by increasing the thickness of FGM from 5 mm to 7.8 mm, the ballistic property of the composite degraded. Also, the strength of the ceramic compositions studied is sufficient to completely fracture the nose of the pointed projectile used. Analysis of the ceramic fragments (2 mu m-10 mm) showed that harder the ceramic, coarser were the fragments formed. On comparing the results with available armor systems, it has been concluded that TiB2 based composites can show better ballistic properties, except B4C. SEM analysis of the fragments obtained after testing with FGM showed formation of cleavage steps as well as presence of intergranular cracks, indicating that the FGM fractured by mixed mode of failure. It can be concluded that the FGM developed has lower ballistic properties compared to its monolith TiB2-20 wt.% Ti.

Non-neutral evolution in non-LEE-encoded type III effectors of attaching and effacing Escherichia coli

Attaching and effacing Escherichia coli (AEEC) employ type III secretion system (T3SS) to secrete effector proteins into host cells and regulate their function. Here we have investigated T3SS genes of AEEC for non-neutral evolution. Our analysis revealed non-neutral evolution in three genes (nleE1, nleB2 and nleD) which encode effector proteins. These genes are located outside the locus of enterocyte effacement (LEE). In general, non-LEE effector genes show greater deviation from neutral evolution than LEE effector genes. These results suggest that effector genes located outside LEE are under greater selection pressure than those present in LEE. (C) 2012 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.

Can the viscosity in astrophysical black hole accretion disks be close to its string theory bound?

String theory and gauge/gravity duality suggest the lower bound of shear viscosity (eta) to entropy density (s) for any matter to be mu h/4 pi k(B), when h and k(B) are reduced Planck and Boltzmann constants respectively and mu <= 1. Motivated by this, we explore eta/s in black hole accretion flows, in order to understand if such exotic flows could be a natural site for the lowest eta/s. Accretion flow plays an important role in black hole physics in identifying the existence of the underlying black hole. This is a rotating shear flow with insignificant molecular viscosity, which could however have a significant turbulent viscosity, generating transport, heat and hence entropy in the flow. However, in presence of strong magnetic field, magnetic stresses can help in transporting matter independent of viscosity, via celebrated Blandford-Payne mechanism. In such cases, energy and then entropy produces via Ohmic dissipation. In,addition, certain optically thin, hot, accretion flows, of temperature greater than or similar to 10(9) K, may be favourable for nuclear burning which could generate/absorb huge energy, much higher than that in a star. We find that eta/s in accretion flows appears to be close to the lower bound suggested by theory, if they are embedded by strong magnetic field or producing nuclear energy, when the source of energy is not viscous effects. A lower bound on eta/s also leads to an upper bound on the Reynolds number of the flow.

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.

Microscopic and dielectric studies of ZnO nanoparticles loaded in ortho-chloropolyaniline nanocomposites

We have studied the preparation of zinc oxide nanoparticles loaded in various weight percentages in ortho-chloropolyaniline by in situ polymerization method. The length of the O-chloropolyaniline tube is found to be 200 nm and diameter is about 150 nm wherein the embedded ZnO nanoparticles is of 13 nm as confirmed from scanning electron microscopy as well as transmission electron microscopy characterizations. The presence of the vibration band of the metal oxide and other characteristic bands confirms that the polymer nanocomposites are characterized by their Fourier transmission infrared spectroscopy. The X-ray diffraction pattern of nanocomposites reveals their polycrystalline nature. Electrical property of nanocomposites is a function of the filler as well as the matrix. Cole-Cole plots reveal the presence of well-defined semicircular arcs at high frequencies which are attributed to the bulk resistance of the material. Among all nanocomposites, 30 wt% shows the low relaxation time of 151 s, and hence it has high conductivity.

Runtime dependence computation and execution of loops on heterogeneous systems

GPUs have been used for parallel execution of DOALL loops. However, loops with indirect array references can potentially cause cross iteration dependences which are hard to detect using existing compilation techniques. Applications with such loops cannot easily use the GPU and hence do not benefit from the tremendous compute capabilities of GPUs. In this paper, we present an algorithm to compute at runtime the cross iteration dependences in such loops. The algorithm uses both the CPU and the GPU to compute the dependences. Specifically, it effectively uses the compute capabilities of the GPU to quickly collect the memory accesses performed by the iterations by executing the slice functions generated for the indirect array accesses. Using the dependence information, the loop iterations are levelized such that each level contains independent iterations which can be executed in parallel. Another interesting aspect of the proposed solution is that it pipelines the dependence computation of the future level with the actual computation of the current level to effectively utilize the resources available in the GPU. We use NVIDIA Tesla C2070 to evaluate our implementation using benchmarks from Polybench suite and some synthetic benchmarks. Our experiments show that the proposed technique can achieve an average speedup of 6.4x on loops with a reasonable number of cross iteration dependences.

Decode-and-forward relay beamforming for secrecy with finite-alphabet input

In this letter, we compute the secrecy rate of decode-and-forward (DF) relay beamforming with finite input alphabet of size M. Source and relays operate under a total power constraint. First, we observe that the secrecy rate with finite-alphabet input can go to zero as the total power increases, when we use the source power and the relay weights obtained assuming Gaussian input. This is because the capacity of an eavesdropper can approach the finite-alphabet capacity of 1/2 log(2) M with increasing total power, due to the inability to completely null in the direction of the eavesdropper. We then propose a transmit power control scheme where the optimum source power and relay weights are obtained by carrying out transmit power (source power plus relay power) control on DF with Gaussian input using semi-definite programming, and then obtaining the corresponding source power and relay weights which maximize the secrecy rate for DF with finite-alphabet input. The proposed power control scheme is shown to achieve increasing secrecy rates with increasing total power with a saturation behavior at high total powers.

Solutions of a system of forced Burgers equation

In this article, we obtain explicit solutions of a system of forced Burgers equation subject to some classes of bounded and compactly supported initial data and also subject to certain unbounded initial data. In a series of papers, Rao and Yadav (2010) 1-3] obtained explicit solutions of a nonhomogeneous Burgers equation in one dimension subject to certain classes of bounded and unbounded initial data. Earlier Kloosterziel (1990) 4] represented the solution of an initial value problem for the heat equation, with initial data in L-2 (R-n, e(vertical bar x vertical bar 2/2)), as a series of self-similar solutions of the heat equation in R-n. Here we express the solutions of certain classes of Cauchy problems for a system of forced Burgers equation in terms of self-similar solutions of some linear partial differential equations. (C) 2013 Elsevier Inc. All rights reserved.

Low complexity joint estimation of synchronization impairments in sparse channel for MIMO-OFDM system

Low complexity joint estimation of synchronization impairments and channel in a single-user MIMO-OFDM system is presented in this paper. Based on a system model that takes into account the effects of synchronization impairments such as carrier frequency offset, sampling frequency offset, and symbol timing error, and channel, a Maximum Likelihood (ML) algorithm for the joint estimation is proposed. To reduce the complexity of ML grid search, the number of received signal samples used for estimation need to be reduced. The conventional channel estimation techniques using Least-Squares (LS) or Maximum a posteriori (MAP) methods fail for the reduced sample under-determined system, which results in poor performance of the joint estimator. The proposed ML algorithm uses Compressed Sensing (CS) based channel estimation method in a sparse fading scenario, where the received samples used for estimation are less than that required for an LS or MAP based estimation. The performance of the estimation method is studied through numerical simulations, and it is observed that CS based joint estimator performs better than LS and MAP based joint estimator. (C) 2013 Elsevier GmbH. All rights reserved.

Progressive fusion of reconstruction algorithms for low latency applications in compressed sensing

Recently, it has been shown that fusion of the estimates of a set of sparse recovery algorithms result in an estimate better than the best estimate in the set, especially when the number of measurements is very limited. Though these schemes provide better sparse signal recovery performance, the higher computational requirement makes it less attractive for low latency applications. To alleviate this drawback, in this paper, we develop a progressive fusion based scheme for low latency applications in compressed sensing. In progressive fusion, the estimates of the participating algorithms are fused progressively according to the availability of estimates. The availability of estimates depends on computational complexity of the participating algorithms, in turn on their latency requirement. Unlike the other fusion algorithms, the proposed progressive fusion algorithm provides quick interim results and successive refinements during the fusion process, which is highly desirable in low latency applications. We analyse the developed scheme by providing sufficient conditions for improvement of CS reconstruction quality and show the practical efficacy by numerical experiments using synthetic and real-world data. (C) 2013 Elsevier B.V. All rights reserved.