Data-resolution based optimal choice of minimum required measurements for image-guided diffuse optical tomography

Image-guided diffuse optical tomography has the advantage of reducing the total number of optical parameters being reconstructed to the number of distinct tissue types identified by the traditional imaging modality, converting the optical image-reconstruction problem from underdetermined in nature to overdetermined. In such cases, the minimum required measurements might be far less compared to those of the traditional diffuse optical imaging. An approach to choose these optimally based on a data-resolution matrix is proposed, and it is shown that such a choice does not compromise the reconstruction performance. (C) 2013 Optical Society of America

Force and ATP hydrolysis dependent regulation of RecA nucleoprotein filament by single-stranded DNA binding protein

In Escherichia coli, the filament of RecA formed on single-stranded DNA (ssDNA) is essential for recombinational DNA repair. Although ssDNA-binding protein (SSB) plays a complicated role in RecA reactions in vivo, much of our understanding of the mechanism is based on RecA binding directly to ssDNA. Here we investigate the role of SSB in the regulation of RecA polymerization on ssDNA, based on the differential force responses of a single 576-nucleotide-long ssDNA associated with RecA and SSB. We find that SSB outcompetes higher concentrations of RecA, resulting in inhibition of RecA nucleation. In addition, we find that pre-formed RecA filaments de-polymerize at low force in an ATP hydrolysis- and SSB-dependent manner. At higher forces, re-polymerization takes place, which displaces SSB from ssDNA. These findings provide a physical picture of the competition between RecA and SSB under tension on the scale of the entire nucleoprotein SSB array, which have broad biological implications particularly with regard to competitive molecular binding.

An Optimal Fuzzy Logic Controller tuned with Artificial Immune System

In this paper, a method for the tuning the membership functions of a Mamdani type Fuzzy Logic Controller (FLC) using the Clonal Selection Algorithm(CSA) a model of the Artificial Immune System(AIS) paradigm is examined. FLC's are designed for two problems, firstly the linear cart centering problem and secondly the highly nonlinear inverted pendulum problem. The FLC tuned by AIS is compared with FLC tuned by GA. In order to check the robustness of the designed PLC's white noise was added to the system, further, the masses of the cart and the length and mass of the pendulum are changed. The PLC's were also tested in the presence of faulty rules. Finally, Kruskal Wallis test was performed to compare the performance of the GA and AIS. An insight into the algorithms are also given by studying the effect of the important parameters of GA and AIS.

Near-optimal large-MIMO detection using randomized MCMC and randomized search algorithms

Low-complexity near-optimal detection of signals in MIMO systems with large number (tens) of antennas is getting increased attention. In this paper, first, we propose a variant of Markov chain Monte Carlo (MCMC) algorithm which i) alleviates the stalling problem encountered in conventional MCMC algorithm at high SNRs, and ii) achieves near-optimal performance for large number of antennas (e.g., 16×16, 32×32, 64×64 MIMO) with 4-QAM. We call this proposed algorithm as randomized MCMC (R-MCMC) algorithm. Second, we propose an other algorithm based on a random selection approach to choose candidate vectors to be tested in a local neighborhood search. This algorithm, which we call as randomized search (RS) algorithm, also achieves near-optimal performance for large number of antennas with 4-QAM. The complexities of the proposed R-MCMC and RS algorithms are quadratic/sub-quadratic in number of transmit antennas, which are attractive for detection in large-MIMO systems. We also propose message passing aided R-MCMC and RS algorithms, which are shown to perform well for higher-order QAM.

Optimal control problem for the time-dependent Kirchhoff-Love plate in a domain with rough boundary

In this paper, we study the asymptotic behavior of an optimal control problem for the time-dependent Kirchhoff-Love plate whose middle surface has a very rough boundary. We identify the limit problem which is an optimal control problem for the limit equation with a different cost functional.

Optimal forwarding in delay tolerant networks with multiple destinations

We study the trade-off 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 packet and the number of destinations that have received the packet. 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 ODE (i.e., 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.

Optimal MSE solution for a decision feedback equalizer

Due to the inherent feedback in a decision feedback equalizer (DFE) the minimum mean square error (MMSE) or Wiener solution is not known exactly. The main difficulty in such analysis is due to the propagation of the decision errors, which occur because of the feedback. Thus in literature, these errors are neglected while designing and/or analyzing the DFEs. Then a closed form expression is obtained for Wiener solution and we refer this as ideal DFE (IDFE). DFE has also been designed using an iterative and computationally efficient alternative called least mean square (LMS) algorithm. However, again due to the feedback involved, the analysis of an LMS-DFE is not known so far. In this paper we theoretically analyze a DFE taking into account the decision errors. We study its performance at steady state. We then study an LMS-DFE and show the proximity of LMS-DFE attractors to that of the optimal DFE Wiener filter (obtained after considering the decision errors) at high signal to noise ratios (SNR). Further, via simulations we demonstrate that, even at moderate SNRs, an LMS-DFE is close to the MSE optimal DFE. Finally, we compare the LMS DFE attractors with IDFE via simulations. We show that an LMS equalizer outperforms the IDFE. In fact, the performance improvement is very significant even at high SNRs (up to 33%), where an IDFE is believed to be closer to the optimal one. Towards the end, we briefly discuss the tracking properties of the LMS-DFE.

Antenna Selection in Interference-Constrained Underlay Cognitive Radios: SEP-Optimal Rule and Performance Benchmarking

In the underlay mode of cognitive radio, secondary users are allowed to transmit when the primary is transmitting, but under tight interference constraints that protect the primary. However, these constraints limit the secondary system performance. Antenna selection (AS)-based multiple antenna techniques, which exploit spatial diversity with less hardware, help improve secondary system performance. We develop a novel and optimal transmit AS rule that minimizes the symbol error probability (SEP) of an average interference-constrained multiple-input-single-output secondary system that operates in the underlay mode. We show that the optimal rule is a non-linear function of the power gain of the channel from the secondary transmit antenna to the primary receiver and from the secondary transmit antenna to the secondary receive antenna. We also propose a simpler, tractable variant of the optimal rule that performs as well as the optimal rule. We then analyze its SEP with L transmit antennas, and extensively benchmark it with several heuristic selection rules proposed in the literature. We also enhance these rules in order to provide a fair comparison, and derive new expressions for their SEPs. The results bring out new inter-relationships between the various rules, and show that the optimal rule can significantly reduce the SEP.

A LSQR-type method provides a computationally efficient automated optimal choice of regularization parameter in diffuse optical tomography

Purpose: Developing a computationally efficient automated method for the optimal choice of regularization parameter in diffuse optical tomography. Methods: The least-squares QR (LSQR)-type method that uses Lanczos bidiagonalization is known to be computationally efficient in performing the reconstruction procedure in diffuse optical tomography. The same is effectively deployed via an optimization procedure that uses the simplex method to find the optimal regularization parameter. The proposed LSQR-type method is compared with the traditional methods such as L-curve, generalized cross-validation (GCV), and recently proposed minimal residual method (MRM)-based choice of regularization parameter using numerical and experimental phantom data. Results: The results indicate that the proposed LSQR-type and MRM-based methods performance in terms of reconstructed image quality is similar and superior compared to L-curve and GCV-based methods. The proposed method computational complexity is at least five times lower compared to MRM-based method, making it an optimal technique. Conclusions: The LSQR-type method was able to overcome the inherent limitation of computationally expensive nature of MRM-based automated way finding the optimal regularization parameter in diffuse optical tomographic imaging, making this method more suitable to be deployed in real-time. (C) 2013 American Association of Physicists in Medicine. http://dx.doi.org/10.1118/1.4792459]

Rice LHS1/OsMADS1 Controls Floret Meristem Specification by Coordinated Regulation of Transcription Factors and Hormone Signaling Pathways

SEPALLATA (SEP) MADS box transcription factors mediate floral development in association with other regulators. Mutants in five rice (Oryza sativa) SEP genes suggest both redundant and unique functions in panicle branching and floret development. LEAFY HULL STERILE1/OsMADS1, from a grass-specific subgroup of LOFSEP genes, is required for specifying a single floret on the spikelet meristem and for floret organ development, but its downstream mechanisms are unknown. Here, key pathways and directly modulated targets of OsMADS1 were deduced from expression analysis after its knockdown and induction in developing florets and by studying its chromatin occupancy at downstream genes. The negative regulation of OsMADS34, another LOFSEP gene, and activation of OsMADS55, a SHORT VEGETATIVE PHASE-like floret meristem identity gene, show its role in facilitating the spikelet-to-floret meristem transition. Direct regulation of other transcription factor genes like OsHB4 (a class III homeodomain Leu zipper member), OsBLH1 (a BEL1-like homeodomain member), OsKANADI2, OsKANADI4, and OsETTIN2 show its role in meristem maintenance, determinacy, and lateral organ development. We found that the OsMADS1 targets OsETTIN1 and OsETTIN2 redundantly ensure carpel differentiation. The multiple effects of OsMADS1 in promoting auxin transport, signaling, and auxin-dependent expression and its direct repression of three cytokinin A-type response regulators show its role in balancing meristem growth, lateral organ differentiation, and determinacy. Overall, we show that OsMADS1 integrates transcriptional and signaling pathways to promote rice floret specification and development.

Regulation of lipid biosynthesis, sliding motility, and biofilm formation by a membrane-anchored nucleoid-associated protein of mycobacterium tuberculosis

Bacteria use a number of small basic proteins for organization and compaction of their genomes. By their interaction with DNA, these nucleoid-associated proteins (NAPs) also influence gene expression. Rv3852, a NAP of Mycobacterium tuberculosis, is conserved among the pathogenic and slow-growing species of mycobacteria. Here, we show that the protein predominantly localizes in the cell membrane and that the carboxy-terminal region with the propensity to form a transmembrane helix is necessary for its membrane localization. The protein is involved in genome organization, and its ectopic expression in Mycobacterium smegmatis resulted in altered nucleoid morphology, defects in biofilm formation, sliding motility, and change in apolar lipid profile. We demonstrate its crucial role in regulating the expression of KasA, KasB, and GroEL1 proteins, which are in turn involved in controlling the surface phenotypes in mycobacteria.

Optimal parameter selection for bilateral filters using Poisson unbiased risk estimate

Bilateral filters perform edge-preserving smoothing and are widely used for image denoising. The denoising performance is sensitive to the choice of the bilateral filter parameters. We propose an optimal parameter selection for bilateral filtering of images corrupted with Poisson noise. We employ the Poisson's Unbiased Risk Estimate (PURE), which is an unbiased estimate of the Mean Squared Error (MSE). It does not require a priori knowledge of the ground truth and is useful in practical scenarios where there is no access to the original image. Experimental results show that quality of denoising obtained with PURE-optimal bilateral filters is almost indistinguishable with that of the Oracle-MSE-optimal bilateral filters.

Regulation of Chemokines, CCL3 and CCL4, by interferon gamma and Nitric oxide synthase 2 in mouse macrophages and during Salmonella enterica Serovar Typhimurium infection

Background. Interferon gamma (IFN-gamma) increases the expression of multiple genes and responses; however, the mechanisms by which IFN-gamma downmodulates cellular responses is not well understood. In this study, the repression of CCL3 and CCL4 by IFN-gamma and nitric oxide synthase 2 (NOS2) in macrophages and upon Salmonella typhimurium infection of mice was investigated. Methods. Small molecule regulators and adherent peritoneal exudates cells (A-PECs) from Nos2(-/-)mice were used to identify the contribution of signaling molecules during IFN-gamma-mediated in vitro regulation of CCL3, CCL4, and CXCL10. In addition, infection of bone marrow-derived macrophages (BMDMs) and mice (C57BL/6, Ifn-gamma(-/), and Nos2(-/-)) with S. typhimurium were used to gain an understanding of the in vivo regulation of these chemokines. Results. IFN-gamma repressed CCL3 and CCL4 in a signal transducer and activator of transcription 1 (STAT1)-NOS2-p38 mitogen activated protein kinase (p38MAPK)-activating transcription factor 3 (ATF3) dependent pathway in A-PECs. Also, during intracellular replication of S. typhimurium in BMDMs, IFN-gamma and NOS2 repressed CCL3 and CCL4 production. The physiological roles of these observations were revealed during oral infection of mice with S. typhimurium, wherein endogenous IFN-gamma and NOS2 enhanced serum amounts of tumor necrosis factor alpha and CXCL10 but repressed CCL3 and CCL4. Conclusions. This study sheds novel mechanistic insight on the regulation of CCL3 and CCL4 in mouse macrophages and during S. typhimurium oral infection.