Ca2+ channel blockers modulate metabolism of collagens within the extracellular matrix.

The extracellular matrix (ECM) is an intricate network composed of an array of macromolecules capable of regulating the functional responsiveness of cells. Its composition greatly varies among different types of tissue, and dysregulation of its metabolism may contribute to vascular remodeling during the pathogenesis of various diseases, including atherosclerosis. In view of their antiatherosclerotic effects, the role of Ca2+ channel blockers in the metabolism of ECM was examined. Nanomolar concentrations of the five Ca2+ channel blockers amlodipine, felodipine, manidipine, verapamil, or diltiazem significantly decreased both the constitutive and platelet-derived growth factor BB-dependent collagen deposition in the ECM formed by human vascular smooth muscle cells and fibroblasts. The drugs inhibited the expression of fibrillar collagens type I and III and of basement membrane type IV collagen. Furthermore, Ca2+ channel blockers specifically increased the proteolytic activity of the 72-kDa type IV collagenase as shown by gelatin zymography and inhibited the transcription of tissue inhibitor of metalloproteinases-2.

A Training-Based Iterative Detection/Channel Estimation Scheme for Large Non-Orthogonal STBC MIMO Systems

In this paper, we propose a training-based channel estimation scheme for large non-orthogonal space-time block coded (STBC) MIMO systems.The proposed scheme employs a block transmission strategy where an N-t x N-t pilot matrix is sent (for training purposes) followed by several N-t x N-t square data STBC matrices, where Nt is the number of transmit antennas. At the receiver, we iterate between channel estimation (using an MMSE estimator) and detection (using a low-complexity likelihood ascent search (LAS) detector) till convergence or for a fixed number of iterations. Our simulation results show that excellent bit error rate and nearness-to-capacity performance are achieved by the proposed scheme at low complexities. The fact that we could show such good results for large STBCs (e.g., 16 x 16 STBC from cyclic division algebras) operating at spectral efficiencies in excess of 20 bps/Hz (even after accounting for the overheads meant for pilot-based channel estimation and turbo coding) establishes the effectiveness of the proposed scheme.

Texture evolution in an Al-Cu alloy during equal channel angular pressing: the effect of starting microstructure

In this article, the effect of initial microstructure on the texture evolution in 2014 Al alloy during equal channel angular pressing (ECAP) through route A has been reported. Three heat treatment conditions were chosen to generate the initial microstructures, namely (i) the recrystallization anneal (as-received), (ii) solution treatment at 768 K for 1 h, and (iii) solution treatment (768 K for 1 h) plus aging at 468 K for 5 h. Texture analyses were performed using orientation distribution function (ODF) method. The texture strength after ECAP processing was different for the three samples in the order, solutionised > solutionised plus aged condition > as-received. The prominent texture components were A (E) /(A) over bar (E) and B(E)/(B) over bar (E) in addition to several weaker components for the three materials. The strong texture evolution in solutionised condition has been attributed to higher strain hardening of the matrix due to higher amount of solute. In case of the as-received as well as solutionised plus aged alloy, the weaker texture could be due to the strain scattering from extensive precipitate fragmentation and dissolution during ECAP.

Completely random nanoporous Cu4O3-CuO-C composite thin films for potential application as multiple channel photonic band gap based filter in the telecommunication wavelengths

In 2003, Babin et al. theoretically predicted (J. Appl. Phys. 94:4244, 2003) that fabrication of organic-inorganic hybrid materials would probably be required to implement structures with multiple photonic band gaps. In tune with their prediction, we report synthesis of such an inorganic-organic nanocomposite, comprising Cu4O3-CuO-C thin films that experimentally exhibit the highest (of any known material) number (as many as eleven) of photonic band gaps in the near infrared. On contrary to the report by Wang et al. (Appl. Phys. Lett. 84:1629, 2004) that photonic crystals with multiple stop gaps require highly correlated structural arrangement such as multilayers of variable thicknesses, we demonstrate experimental realization of multiple stop gaps in completely randomized structures comprising inorganic oxide nanocrystals (Cu4O3 and CuO) randomly embedded in a randomly porous carbonaceous matrix. We report one step synthesis of such nanostructured films through the metalorganic chemical vapor deposition technique using a single source metalorganic precursor, Cu-4(deaH)(dea)(oAc)(5) a <...aEuro parts per thousand(CH3)(2)CO. The films displaying multiple (4/9/11) photonic band gaps with equal transmission losses in the infrared are promising materials to find applications as multiple channel photonic band gap based filter for WDM technology.

Bounds on the sum-rate capacity of the Gaussian MIMO X channel

We consider the MIMO X channel (XC), a system consisting of two transmit-receive pairs, where each transmitter communicates with both the receivers. Both the transmitters and receivers are equipped with multiple antennas. First, we derive an upper bound on the sum-rate capacity of the MIMO XC under individual power constraint at each transmitter. The sum-rate capacity of the two-user multiple access channel (MAC) that results when receiver cooperation is assumed forms an upper bound on the sum-rate capacity of the MIMO XC. We tighten this bound by considering noise correlation between the receivers and deriving the worst noise covariance matrix. It is shown that the worst noise covariance matrix is a saddle-point of a zero-sum, two-player convex-concave game, which is solved through a primal-dual interior point method that solves the maximization and the minimization parts of the problem simultaneously. Next, we propose an achievable scheme which employs dirty paper coding at the transmitters and successive decoding at the receivers. We show that the derived upper bound is close to the achievable region of the proposed scheme at low to medium SNRs.

Molecular Insights Revealing Interaction of Tim23 and Channel Subunits of Presequence Translocase

Tim23 is an essential channel-forming subunit of the presequence translocase recruiting multiple components for assembly of the core complex, thereby regulating the protein translocation process. However, understanding of the precise interaction of subunits associating with Tim23 remains largely elusive. Our findings highlight that transmembrane helix 1 (TM1) is required for homodimerization of Tim23, while, together with TM2, it is involved in preprotein binding within the channel. Based on our evidence, we predict that the TM1 and TM2 from each dimer are involved in the formation of the central translocation pore, aided by Tim17. Furthermore, TM2 is also involved in the recruitment of Tim21 and the presequence-associated motor (PAM) subcomplex to the Tim23 channel, while the matrix-exposed loop L1 generates specificity in their association with the core complex. Strikingly, our findings indicate that the C-terminal sequence of Tim23 is dispensable for growth and functions as an inhibitor for binding of Tim21. Our model conceptually explains the cooperative function between Tam41 and Pam17 subunits, while the antagonistic activity of Tim21 predominantly determines the bound and free forms of the PAM subcomplex during import.

Channel estimation at the transmitter in a reciprocal MIMO spatial multiplexing system

This paper considers the problem of channel estimation at the transmitter in a spatial multiplexing-based Time Division Duplex (TDD) Multiple Input Multiple Output (MIMO) system with perfect CSIR. A novel channel-dependent Reverse Channel Training (RCT) sequence is proposed, using which the transmitter estimates the beamforming vectors for forward link data transmission. This training sequence is designed based on the following two metrics: (i) a capacity lower bound, and (ii) the mean square error in the estimate. The performance of the proposed training scheme is analyzed and is shown to significantly outperform the conventional orthogonal RCT sequence. Also, in the case where the transmitter uses water-filling power allocation for data transmission, a novel RCT sequence is proposed and optimized with respect to the MSE in estimating the transmit covariance matrix.

Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning

It is well known that the impulse response of a wide-band wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.

Channel Hardening-Exploiting Message Passing (CHEMP) Receiver in Large-Scale MIMO Systems

In this paper, we propose a multiple-input multiple-output (MIMO) receiver algorithm that exploits channel hardening that occurs in large MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of the matrix become increasingly weaker compared to the diagonal terms as the size of the channel gain matrix increases. Specifically, we propose a message passing detection (MPD) algorithm which works with the real-valued matched filtered received vector (whose signal term becomes, where is the transmitted vector), and uses a Gaussian approximation on the off-diagonal terms of the matrix. We also propose a simple estimation scheme which directly obtains an estimate of (instead of an estimate of), which is used as an effective channel estimate in the MPD algorithm. We refer to this receiver as the channel hardening-exploiting message passing (CHEMP) receiver. The proposed CHEMP receiver achieves very good performance in large-scaleMIMO systems (e.g., in systems with 16 to 128 uplink users and 128 base station antennas). For the considered large MIMO settings, the complexity of the proposed MPD algorithm is almost the same as or less than that of the minimum mean square error (MMSE) detection. This is because the MPD algorithm does not need a matrix inversion. It also achieves a significantly better performance compared to MMSE and other message passing detection algorithms using MMSE estimate of. Further, we design optimized irregular low density parity check (LDPC) codes specific to the considered large MIMO channel and the CHEMP receiver through EXIT chart matching. The LDPC codes thus obtained achieve improved coded bit error rate performance compared to off-the-shelf irregular LDPC codes.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Power Allocation in MIMO Wiretap Channel with Statistical CSI and Finite-Alphabet Input

In this paper, we consider the problem of power allocation in MIMO wiretap channel for secrecy in the presence of multiple eavesdroppers. Perfect knowledge of the destination channel state information (CSI) and only the statistical knowledge of the eavesdroppers CSI are assumed. We first consider the MIMO wiretap channel with Gaussian input. Using Jensen's inequality, we transform the secrecy rate max-min optimization problem to a single maximization problem. We use generalized singular value decomposition and transform the problem to a concave maximization problem which maximizes the sum secrecy rate of scalar wiretap channels subject to linear constraints on the transmit covariance matrix. We then consider the MIMO wiretap channel with finite-alphabet input. We show that the transmit covariance matrix obtained for the case of Gaussian input, when used in the MIMO wiretap channel with finite-alphabet input, can lead to zero secrecy rate at high transmit powers. We then propose a power allocation scheme with an additional power constraint which alleviates this secrecy rate loss problem, and gives non-zero secrecy rates at high transmit powers.

Birefringence of UV-written channel waveguides

The combination of the effective index method and the transfer matrix method is adopted to calculate the indices of quasi-TE and quasi-TM modes in a UV-written channel waveguide, and the difference between the indices is used to characterize its birefringence. The dimensions, the ratio of width to thickness, the original index of the core layer, the index of the cladding, and the index profile are all taken into account. The simulation results indicate that the birefringence decreases with increasing dimensions, ratio of width to thickness, and indices of the cladding; on the contrary, increases of the original index of the core layer and of the vertical index gradient intensified the birefringence. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Accurate mode analysis of ultraviolet-written channel waveguides

The transfer matrix method combined with the effective index method is adopted to model the silica-based channel waveguide patterned by UV writing. The effective indexes of the graded index channel waveguides with different dimension are calculated. The maximal error of the effective index is less than 3 x 10(-5). By this method, the number of the guided mode and the dimension range to guide certain modes can be obtained easily. Finally, the dimension range to guide a single mode is presented. (c) 2005 Society of Photo-Optical Instrumentation Engineers.

Channel formation and intermediate range order in sodium silicate melts and glasses

Kargl, Florian; Meyer, A.; Horbach, J.; Kob, W., (2004) 'Channel formation and intermediate range order in sodium silicate melts and glasses', Physical Review Letters 93(2) pp.027801 RAE2008

Amplitude banded RLS approach to time variant channel equalization

This paper proposes a non-linear adaptive algorithm, the amplitude banded RLS (ABRLS) algorithm, as an adaptation procedure for time variant channel equalizers. In the ABRLS algorithm, a coefficient matrix is updated based on the amplitude level of the received sequence. To enhance the capability of tracking for the ABRLS algorithm, a parallel adaptation scheme is utilized which involves the structures of decision feedback equalizer (DFE). Computer simulations demonstrate that the novel ABRLS based equalizer provides a significant improvement relative to the conventional RLS DFE on a rapidly time variant communication channel.