Signal-Powered Low-Drop-Diode Equivalent Circuit for Full-Wave Bridge Rectifier

Piezoelectric-device-based vibration energy harvesting requires a rectifier for conversion of input ac to usable dc form. Power loss due to diode drop in rectifier is a significant fraction of the already low levels of harvested power. The proposed circuit is a low-drop-diode equivalent, which mimics a diode using linear region-operated MOSFET. The proposed diode equivalent is powered directly from input signal and requires no additional power supply for its control. Power used by the control circuit is kept at a bare minimum to have an overall output power improvement. Diode equivalent was used to replace the four diodes in a full-wave bridge rectifier, which is the basic full- wave rectifier and is a part of the more advanced rectifiers like switch-only and bias-flip rectifiers. Simulation in 130-nm technology and experiment with discrete components show that a bridge rectifier with the proposed diode provides a 30-169% increase in output power extracted from piezoelectric device, as compared to a bridge rectifier with diode-connected MOSFETs. The bridge rectifier with the proposed diode can extract 90% of the maximum available power from an ideal piezoelectric device-bridge rectifier circuit. Setting aside the constraint of power loss, simulations indicate that diode drop as low as 10 mV at 38 mu A can be achieved.

A touch of history and a peep into the future of the lipid-quinone known as coenzyme Q and ubiquinone

Coenzyme Q (ubiquinone), a fully substituted benzoquinone with polyprenyl side chain, participates in many cellular redox activities. Paradoxically it was discovered only in 1957, albeit being ubiquitous. It required a person, F. L. Crane, a place, Enzyme Institute, Madison, USA, and a time when D. E. Green was directing vigorous research on mitochondria. Located at the transition of 2-electron flavoproteins and 1-electron cytochrome carriers, it facilitates electron transfer through the elegant Q-cycle in mitochondria to reduce O-2 to H2O, and to H2O2, now a significant signal-transducing agent, as a minor activity in shunt pathway (animals) and alternative oxidase (plants). The ability to form Q-radical by losing an electron and a proton was ingeniously used by Mitchell to explain the formation of the proton gradient, considered the core of energy transduction, and also in acidification in vacuoles. Known to be a mobile membrane constituent (microsomes, plasma membrane and Golgi apparatus), allowing it to reach multiple sites, coenzyme Q is expected to have other activities. Coenzyme Q protects circulating lipoproteins being a better lipid antioxidant than even vitamin E. Binding to proteins such as QPS, QPN, QPC and uncoupling protein in mitochondria, QA and QB in the reaction centre in R. sphaeroides, and disulfide bond-forming protein in E. coli (possibly also in Golgi), coenzyme Q acquires selective functions. A characteristic of orally dosed coenzyme Q is its exclusive absorption into the liver, but not the other tissues. This enrichment of Q is accompanied by significant decrease of blood pressure and of serum cholesterol. Inhibition of formation of mevalonate, the common precursor in the branched isoprene pathway, by the minor product, coenzyme Q, decreases the major product, cholesterol. Relaxation of contracted arterial smooth muscle by a side-chain truncated product of coenzyme Q explains its effect of decreasing blood pressure. Extensive clinical studies carried out on oral supplements of coenzyine Q, initially by K. Folkers and Y. Yamamura and followed many others, revealed a large number of beneficial effects, significantly in cardiovascular diseases. Such a variety of effects by this lipid quinone cannot depend on redox activity alone. The fat-soluble vitamins (A, D, E and K) that bear structural relationship with coenzyme Q are known to be active in their polar forms. A vignette of modified forms of coenzyme Q taking active role in its multiple effects is emerging.

Crowd Sourcing a New Paradigm for Interactome Driven Drug Target Identification in Mycobacterium tuberculosis

A decade since the availability of Mycobacterium tuberculosis (Mtb) genome sequence, no promising drug has seen the light of the day. This not only indicates the challenges in discovering new drugs but also suggests a gap in our current understanding of Mtb biology. We attempt to bridge this gap by carrying out extensive re-annotation and constructing a systems level protein interaction map of Mtb with an objective of finding novel drug target candidates. Towards this, we synergized crowd sourcing and social networking methods through an initiative `Connect to Decode' (C2D) to generate the first and largest manually curated interactome of Mtb termed `3interactome pathway' (IPW), encompassing a total of 1434 proteins connected through 2575 functional relationships. Interactions leading to gene regulation, signal transduction, metabolism, structural complex formation have been catalogued. In the process, we have functionally annotated 87% of the Mtb genome in context of gene products. We further combine IPW with STRING based network to report central proteins, which may be assessed as potential drug targets for development of drugs with least possible side effects. The fact that five of the 17 predicted drug targets are already experimentally validated either genetically or biochemically lends credence to our unique approach.

A Technique to Compute Smooth Amplitude, Phase, and Frequency Modulations From the Analytic Signal

Gabor's analytic signal (AS) is a unique complex signal corresponding to a real signal, but in general, it admits infinitely-many combinations of amplitude and frequency modulations (AM and FM, respectively). The standard approach is to enforce a non-negativity constraint on the AM, but this results in discontinuities in the corresponding phase modulation (PM), and hence, an FM with discontinuities particularly when the underlying AM-FM signal is over-modulated. In this letter, we analyze the phase discontinuities and propose a technique to compute smooth AM and FM from the AS, by relaxing the non-negativity constraint on the AM. The proposed technique is effective at handling over-modulated signals. We present simulation results to support the theoretical calculations.

A CMOS Gas Sensor Array Platform With Fourier Transform Based Impedance Spectroscopy

A CMOS gas sensor array platform with digital read-out containing 27 sensor pixels and a reference pixel is presented. A signal conditioning circuit at each pixel includes digitally programmable gain stages for sensor signal amplification followed by a second order continuous time delta sigma modulator for digitization. Each sensor pixel can be functionalized with a distinct sensing material that facilitates transduction based on impedance change. Impedance spectrum (up to 10 KHz) of the sensor is obtained off-chip by computing the fast Fourier transform of sensor and reference pixel outputs. The reference pixel also compensates for the phase shift introduced by the signal processing circuits. The chip also contains a temperature sensor with digital readout for ambient temperature measurement. A sensor pixel is functionalized with polycarbazole conducting polymer for sensing volatile organic gases and measurement results are presented. The chip is fabricated in a 0.35 CMOS technology and requires a single step post processing for functionalization. It consumes 57 mW from a 3.3 V supply.

The origins of the evolutionary signal used to predict protein-protein interactions

Background: The correlation of genetic distances between pairs of protein sequence alignments has been used to infer protein-protein interactions. It has been suggested that these correlations are based on the signal of co-evolution between interacting proteins. However, although mutations in different proteins associated with maintaining an interaction clearly occur (particularly in binding interfaces and neighbourhoods), many other factors contribute to correlated rates of sequence evolution. Proteins in the same genome are usually linked by shared evolutionary history and so it would be expected that there would be topological similarities in their phylogenetic trees, whether they are interacting or not. For this reason the underlying species tree is often corrected for. Moreover processes such as expression level, are known to effect evolutionary rates. However, it has been argued that the correlated rates of evolution used to predict protein interaction explicitly includes shared evolutionary history; here we test this hypothesis. Results: In order to identify the evolutionary mechanisms giving rise to the correlations between interaction proteins, we use phylogenetic methods to distinguish similarities in tree topologies from similarities in genetic distances. We use a range of datasets of interacting and non-interacting proteins from Saccharomyces cerevisiae. We find that the signal of correlated evolution between interacting proteins is predominantly a result of shared evolutionary rates, rather than similarities in tree topology, independent of evolutionary divergence. Conclusions: Since interacting proteins do not have tree topologies that are more similar than the control group of non-interacting proteins, it is likely that coevolution does not contribute much to, if any, of the observed correlations.

SPARSE SIGNAL RECONSTRUCTION BASED ON SIGNAL DEPENDENT NON-UNIFORM SAMPLES

The classical approach to A/D conversion has been uniform sampling and we get perfect reconstruction for bandlimited signals by satisfying the Nyquist Sampling Theorem. We propose a non-uniform sampling scheme based on level crossing (LC) time information. We show stable reconstruction of bandpass signals with correct scale factor and hence a unique reconstruction from only the non-uniform time information. For reconstruction from the level crossings we make use of the sparse reconstruction based optimization by constraining the bandpass signal to be sparse in its frequency content. While overdetermined system of equations is resorted to in the literature we use an undetermined approach along with sparse reconstruction formulation. We could get a reconstruction SNR > 20dB and perfect support recovery with probability close to 1, in noise-less case and with lower probability in the noisy case. Random picking of LC from different levels over the same limited signal duration and for the same length of information, is seen to be advantageous for reconstruction.

Computational studies on histidine kinase protein BaeS to target multidrug-resistant Salmonella

Multidrug-resistant Salmonella serovars have been a recent concern in curing infectious diseases like typhoid. Salmonella BaeS and BaeR are the two-component system (TCS) that signal transduction proteins found to play an important role in its multidrug resistance. A canonical TCS comprises a histidine kinase (HK) and its cognate partner response regulator (RR). The general approaches for therapeutic targeting are either the catalytic ATP-binding domain or the dimerization domain HisKA (DHp) of the HK, and in some cases, the receiver or the regulatory domain of the RR proteins. Earlier efforts of identifying novel drugs targeting the signal transduction protein have not been quite successful, as it shares similar ATP-binding domain with the key house keeping gene products of the mammalian GHL family. However, targeting the dimerization domain of HisKA through which the signals are received from the RR can be a better approach. In this article, we show stepwise procedure to specifically identify the key interacting residues involved in the dimerization with the RR along with effective targeting by ligands screened from the public database. We have found a few inhibitors which target effectively the important residues for the dimerization activity. Our results suggest a plausible de novo design of better DHp domain inhibitors.

Robust GNSS signal detection in the presence of navigation data bits

This paper considers the problem of weak signal detection in the presence of navigation data bits for Global Navigation Satellite System (GNSS) receivers. Typically, a set of partial coherent integration outputs are non-coherently accumulated to combat the effects of model uncertainties such as the presence of navigation data-bits and/or frequency uncertainty, resulting in a sub-optimal test statistic. In this work, the test-statistic for weak signal detection is derived in the presence of navigation data-bits from the likelihood ratio. It is highlighted that averaging the likelihood ratio based test-statistic over the prior distributions of the unknown data bits and the carrier phase uncertainty leads to the conventional Post Detection Integration (PDI) technique for detection. To improve the performance in the presence of model uncertainties, a novel cyclostationarity based sub-optimal PDI technique is proposed. The test statistic is analytically characterized, and shown to be robust to the presence of navigation data-bits, frequency, phase and noise uncertainties. Monte Carlo simulation results illustrate the validity of the theoretical results and the superior performance offered by the proposed detector in the presence of model uncertainties.

A finite-rate-of-innovation signal sampling perspective of the source-filter model of speech production

We consider the speech production mechanism and the asso- ciated linear source-filter model. For voiced speech sounds in particular, the source/glottal excitation is modeled as a stream of impulses and the filter as a cascade of second-order resonators. We show that the process of sampling speech signals can be modeled as filtering a stream of Dirac impulses (a model for the excitation) with a kernel function (the vocal tract response),and then sampling uniformly. We show that the problem of esti- mating the excitation is equivalent to the problem of recovering a stream of Dirac impulses from samples of a filtered version. We present associated algorithms based on the annihilating filter and also make a comparison with the classical linear prediction technique, which is well known in speech analysis. Results on synthesized as well as natural speech data are presented.

Some new results on signal reconstruction from Fourier transform magnitude spectrum

We address the problem of signal reconstruction from Fourier transform magnitude spectrum. The problem arises in many real-world scenarios where magnitude-only measurements are possible, but it is required to construct a complex-valued signal starting from those measurements. We present some new general results in this context and show that the previously known results on minimum-phase rational transfer functions, and recoverability of minimum-phase functions from magnitude spectrum, form special cases of the results reported in this paper. Some simulation results are also provided to demonstrate the practical feasibility of the reconstruction methodology.

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.

Effect of signal peptide on stability and folding of escherichia coli thioredoxin

The signal peptide plays a key role in targeting and membrane insertion of secretory and membrane proteins in both prokaryotes and eukaryotes. In E. coli, recombinant proteins can be targeted to the periplasmic space by fusing naturally occurring signal sequences to their N-terminus. The model protein thioredoxin was fused at its N-terminus with malE and pelB signal sequences. While WT and the pelB fusion are soluble when expressed, the malE fusion was targeted to inclusion bodies and was refolded in vitro to yield a monomeric product with identical secondary structure to WT thioredoxin. The purified recombinant proteins were studied with respect to their thermodynamic stability, aggregation propensity and activity, and compared with wild type thioredoxin, without a signal sequence. The presence of signal sequences leads to thermodynamic destabilization, reduces the activity and increases the aggregation propensity, with malE having much larger effects than pelB. These studies show that besides acting as address labels, signal sequences can modulate protein stability and aggregation in a sequence dependent manner.

Cognitive radio implementation for a frequency hopping primary signal

Frequency hopping communications, used in the military present significant opportunities for spectrum reuse via the cognitive radio technology. We propose a MAC which incorporates hop instant identification, and supports network discovery and formation, QOS Scheduling and secondary communications. The spectrum sensing algorithm is optimized to deal with the problem of spectral leakage. The algorithms are implemented in a SDR platform based test bed and measurement results are presented.