Ultrasound-modulated optical tomography: recovery of amplitude of vibration in the insonified region from boundary measurement of light correlation

We address a certain inverse problem in ultrasound-modulated optical tomography: the recovery of the amplitude of vibration of scatterers [p(r)] in the ultrasound focal volume in a diffusive object from boundary measurement of the modulation depth (M) of the amplitude autocorrelation of light [phi(r, tau)] traversing through it. Since M is dependent on the stiffness of the material, this is the precursor to elasticity imaging. The propagation of phi(r, tau) is described by a diffusion equation from which we have derived a nonlinear perturbation equation connecting p(r) and refractive index modulation [Delta n(r)] in the region of interest to M measured on the boundary. The nonlinear perturbation equation and its approximate linear counterpart are solved for the recovery of p(r). The numerical results reveal regions of different stiffness, proving that the present method recovers p(r) with reasonable quantitative accuracy and spatial resolution. (C) 2011 Optical Society of America

Bayesian framework and message passing for joint support and signal recovery of approximately sparse signals

In this paper, we develop a low-complexity message passing algorithm for joint support and signal recovery of approximately sparse signals. The problem of recovery of strictly sparse signals from noisy measurements can be viewed as a problem of recovery of approximately sparse signals from noiseless measurements, making the approach applicable to strictly sparse signal recovery from noisy measurements. The support recovery embedded in the approach makes it suitable for recovery of signals with same sparsity profiles, as in the problem of multiple measurement vectors (MMV). Simulation results show that the proposed algorithm, termed as JSSR-MP (joint support and signal recovery via message passing) algorithm, achieves performance comparable to that of sparse Bayesian learning (M-SBL) algorithm in the literature, at one order less complexity compared to the M-SBL algorithm.

Smart polymer mediated purification and recovery of active proteins from inclusion bodies

Obtaining correctly folded proteins from inclusion bodies of recombinant proteins expressed in bacterial hosts requires solubilization with denaturants and a refolding step. Aggregation competes with the second step. Refolding of eight different proteins was carried out by precipitation with smart polymers. These proteins have different molecular weights, different number of disulfide bridges and some of these are known to be highly prone to aggregation. A high throughput refolding screen based upon fluorescence emission maximum around 340 nm (for correctly folded proteins) was developed to identify the suitable smart polymer. The proteins could be dissociated and recovered after the refolding step. The refolding could be scaled up and high refolding yields in the range of 8 mg L-1 (for CD4D12, the first two domains of human CD4) to 58 mg L-1 (for malETrx, thioredoxin fused with signal peptide of maltose binding protein) were obtained. Dynamic light scattering (DLS) showed that polymer if chosen correctly acted as a pseuclochaperonin and bound to the proteins. It also showed that the time for maximum binding was about 50 min which coincided with the time required for incubation (with the polymer) before precipitation for maximum recovery of folded proteins. The refolded proteins were characterized by fluorescence emission spectra, circular dichroism (CD) spectroscopy, melting temperature (T-m), and surface hydrophobicity measurement by ANS (8-anilinol-naphthalene sulfonic acid) fluorescence. Biological activity assay for thioredoxin and fluorescence based assay in case of maltose binding protein (MBP) were also carried out to confirm correct refolding. (C) 2012 Elsevier B.V. All rights reserved.

Optimal multi-layered congestion based pricing schemes for enhanced QoS

Pricing is an effective tool to control congestion and achieve quality of service (QoS) provisioning for multiple differentiated levels of service. In this paper, we consider the problem of pricing for congestion control in the case of a network of nodes with multiple queues and multiple grades of service. We present a closed-loop multi-layered pricing scheme and propose an algorithm for finding the optimal state dependent price levels for individual queues, at each node. This is different from most adaptive pricing schemes in the literature that do not obtain a closed-loop state dependent pricing policy. The method that we propose finds optimal price levels that are functions of the queue lengths at individual queues. Further, we also propose a variant of the above scheme that assigns prices to incoming packets at each node according to a weighted average queue length at that node. This is done to reduce frequent price variations and is in the spirit of the random early detection (RED) mechanism used in TCP/IP networks. We observe in our numerical results a considerable improvement in performance using both of our schemes over that of a recently proposed related scheme in terms of both throughput and delay performance. In particular, our first scheme exhibits a throughput improvement in the range of 67-82% among all routes over the above scheme. (C) 2011 Elsevier B.V. All rights reserved.

Anaerobic retting of banana and arecanut wastes in a plug flow digester for recovery of fiber, biogas and compost

Leaves and leaf sheath of banana and areca husk (Areca catechu) constitute an important component of urban solid waste (USW) in India which are difficult to degrade under normal windrow composting conditions. A successful method of anaerobic digestion built around the fermentation properties of these feedstock has been evolved which uses no moving parts, pretreatment or energy input while enabling recovery of four products: fiber, biogas, compost and pest repellent. An SRT of 27 d and 35 d was found to be optimum for fiber recovery for banana leaf and areca husk, respectively. Banana leaf showed a degradation pattern different from other leaves with slow pectin-1 degradation (80%) and 40% lignin removal in 27 d SRT. Areca husk however, showed a degradation pattern similar to other plant biomass. Mass recovery levels for banana leaf were fiber-20%, biogas-70% (400 ml/g TS) and compost-10%. For areca husk recovery was fiber-50%, biogas-45% (250 ml/g TS) and compost-5%. (C) 2012 Elsevier Inc. All rights reserved.

Effective contrast recovery in rapid dynamic near-infrared diffuse optical tomography using l(1)-norm-based linear image reconstruction method

Traditional image reconstruction methods in rapid dynamic diffuse optical tomography employ l(2)-norm-based regularization, which is known to remove the high-frequency components in the reconstructed images and make them appear smooth. The contrast recovery in these type of methods is typically dependent on the iterative nature of method employed, where the nonlinear iterative technique is known to perform better in comparison to linear techniques (noniterative) with a caveat that nonlinear techniques are computationally complex. Assuming that there is a linear dependency of solution between successive frames resulted in a linear inverse problem. This new framework with the combination of l(1)-norm based regularization can provide better robustness to noise and provide better contrast recovery compared to conventional l(2)-based techniques. Moreover, it is shown that the proposed l(1)-based technique is computationally efficient compared to its counterpart (l(2)-based one). The proposed framework requires a reasonably close estimate of the actual solution for the initial frame, and any suboptimal estimate leads to erroneous reconstruction results for the subsequent frames.

Analytical model for congestion control and throughput with TCP CUBIC connections

We develop a Markov model for a TCP CUBIC connection. Next we use it to obtain approximate expressions for throughput when there may be queuing in the network. Finally we provide the throughputs different TCP CUBIC and TCP NewReno connections obtain while sharing a channel when they may have different round trip delays and packet loss probabilities.

Network congestion management by fuzzy inference using virtual flows

Effective network overload alleviation is very much essential in order to maintain security and integrity from the operational viewpoint of deregulated power systems. This paper aims at developing a methodology to reschedule the active power generation from the sources in order to manage the network congestion under normal/contingency conditions. An effective method has been proposed using fuzzy rule based inference system. Using virtual flows concept, which provides partial contributions/counter flows in the network elements is used as a basis in the proposed method to manage network congestions to the possible extent. The proposed method is illustrated on a sample 6 bus test system and on modified IEEE 39 bus system.

Operational inferences on VANETs in 802.16e and 802.11p with improved performance by Congestion alert

Mobile WiMAX is a burgeoning network technology with diverse applications, one of them being used for VANETs. The performance metrics such as Mean Throughput and Packet Loss Ratio for the operations of VANETs adopting 802.16e are computed through simulation techniques. Next we evaluated the similar performance of VANETs employing 802.11p, also known as WAVE (Wireless Access in Vehicular Environment). The simulation model proposed is close to reality as we have generated mobility traces for both the cases using a traffic simulator (SUMO), and fed it into network simulator (NS2) based on their operations in a typical urban scenario for VANETs. In sequel, a VANET application called `Street Congestion Alert' is developed to assess the performances of these two technologies. For this application, TraCI is used for coupling SUMO and NS2 in a feedback loop to set up a realistic simulation scenario. Our inferences show that the Mobile WiMAX performs better than WAVE for larger network sizes.

Noniterative inversion strategy for photoacoustic tomography: recovery of absorbed energy map from boundary pressure measurements

The inverse problem in photoacoustic tomography (PAT) seeks to obtain the absorbed energy map from the boundary pressure measurements for which computationally intensive iterative algorithms exist. The computational challenge is heightened when the reconstruction is done using boundary data split into its frequency spectrum to improve source localization and conditioning of the inverse problem. The key idea of this work is to modify the update equation wherein the Jacobian and the perturbation in data are summed over all wave numbers, k, and inverted only once to recover the absorbed energy map. This leads to a considerable reduction in the overall computation time. The results obtained using simulated data, demonstrates the efficiency of the proposed scheme without compromising the accuracy of reconstruction.

Quick recovery in transactional flash

Maintaining metadata consistency is a critical issue in designing a filesystem. Although satisfactory solutions are available for filesystems residing on magnetic disks, these solutions may not give adequate performance for filesystems residing on flash devices. Prabhakaran et al. have designed a metadata consistency mechanism specifically for flash chips, called Transactional Flash1]. It uses cyclic commit mechanism to provide transactional abstractions. Although significant improvement over usual journaling techniques, this mechanism has certain drawbacks such as complex protocol and necessity to read whole flash during recovery, which slows down recovery process. In this paper we propose addition of thin journaling layer on top of Transactional Flash to simplify the protocol and speed up the recovery process. The simplified protocol named Quick Recovery Cyclic Commit (QRCC) uses journal stored on NOR flash for recovery. Our evaluations on actual raw flash card show that journal writes add negligible penalty compared to original Transactional Flash's write performance, while quick recovery is facilitated by journal in case of failures.

Temperature dependence of indentation recovery ratios in austenitic and martensitic shape memory alloys

Instrumented microindentation (IM) on two Ni-Ti shape memory alloys (SMAs), where one is austenitic and the other is martensitic at room temperature, were conducted from 40 to 150 degrees C. Results show that the depth and work recovery ratios, eta(d) and eta(w) respectively, are complementary to each other. While eta(d) decreases gradually with temperature for austenite, it drops markedly for the martensite in the martensite-to-austenite transformation regime. These results affirm the utility of IM for characterizing SMAs.