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.

A cyclic peptide mimic of an RNA recognition motif of human La protein is a potent inhibitor of hepatitis C virus

Due to limited available therapeutic options, developing new lead compounds against hepatitis C virus is an urgent need. Human La protein stimulates hepatitis C virus translation through interaction with the hepatitis C viral RNA. A cyclic peptide mimicking the beta-turn of the human La protein that interacts with the viral RNA was synthesized. It inhibits hepatitis C viral RNA translation significantly better than the corresponding linear peptide at longer post-treatment times. The cyclic peptide also inhibited replication as measured by replicon RNA levels using real time RT-PCR. The cyclic peptide emerges as a promising lead compound against hepatitis C.

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.

Designed three-stranded beta-sheet in an alpha/beta hybrid peptide

The incorporation of beta-amino acid residues into the antiparallel beta-strand segments of a multi-stranded beta-sheet peptide is demonstrated for a 19-residue peptide, Boc-LV(beta)FV(D)PGL(beta)FVVL(D)PGLVL(beta)FVV-OMe (BBH19). Two centrally positioned (D)Pro-Gly segments facilitate formation of a stable three-stranded beta-sheet, in which beta-phenylalanine ((beta)Phe) residues occur at facing positions 3, 8 and 17. Structure determination in methanol solution is accomplished by using NMR-derived restraints obtained from NOEs, temperature dependence of amide NH chemical shifts, rates of H/D exchange of amide protons and vicinal coupling constants. The data are consistent with a conformationally well-defined three-stranded beta-sheet structure in solution. Cross-strand interactions between (beta)Phe3/(beta)Phe17 and (beta)Phe3/Val15 residues define orientations of these side-chains. The observation of close contact distances between the side-chains on the N- and C-terminal strands of the three-stranded beta-sheet provides strong support for the designed structure. Evidence is presented for multiple side-chain conformations from an analysis of NOE data. An unusual observation of the disappearance of the Gly NH resonances upon prolonged storage in methanol is rationalised on the basis of a slow aggregation step, resulting in stacking of three-stranded beta-sheet structures, which in turn influences the conformational interconversion between type I' and type II' beta-turns at the two (D)Pro-Gly segments. Experimental evidence for these processes is presented. The decapeptide fragment Boc-LV(beta)FV(D)PGL(beta)FVV-OMe (BBH10), which has been previously characterized as a type I' beta-turn nucleated hairpin, is shown to favour a type II' beta-turn conformation in solution, supporting the occurrence of conformational interconversion at the turn segments in these hairpin and sheet structures.

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.

Single electron transfer-driven multi-dimensional signal read-out function of TCNQ as an ``off-the-shelf'' detector for cyanide

Herein we report the first applications of TCNQ as a rapid and highly sensitive off-the-shelf cyanide detector. As a proof-of-concept, we have applied a kinetically selective single-electron transfer (SET) from cyanide to deep-lying LUMO orbitals of TCNQ to generate a persistently stable radical anion (TCNQ(center dot-)), under ambient condition. In contrast to the known cyanide sensors that operate with limited signal outputs, TCNQ(center dot-) offers a unique multiple signaling platform. The signal readability is facilitated through multichannel absorption in the UV-vis-NIR region and scattering-based spectroscopic methods like Raman spectroscopy and hyper Rayleigh scattering techniques. Particularly notable is the application of the intense 840 nm NIR absorption band to detect cyanide. This can be useful for avoiding background interference in the UV-vis region predominant in biological samples. We also demonstrate the fabrication of a practical electronic device with TCNQ as a detector. The device generates multiorder enhancement in current with cyanide because of the formation of the conductive TCNQ(center dot-).

Stabilizing effect of electrostatic vs. aromatic interactions in diproline nucleated peptide beta-hairpins

The contribution of Tyr-His vs. Cys-His interacting pairs to the scaffold stability of (D)Pro-(L)Pro nucleated peptide beta-hairpins has been examined. We present direct evidence for the superiority of the Cys-His pairs, mediated by sulphur-imidazole interactions, as added stabilizing agents of the beta-hairpin scaffold.

Narrowband signal detection techniques in shallow ocean by acoustic vector sensor array

This paper presents the formulation and performance analysis of four techniques for detection of a narrowband acoustic source in a shallow range-independent ocean using an acoustic vector sensor (AVS) array. The array signal vector is not known due to the unknown location of the source. Hence all detectors are based on a generalized likelihood ratio test (GLRT) which involves estimation of the array signal vector. One non-parametric and three parametric (model-based) signal estimators are presented. It is shown that there is a strong correlation between the detector performance and the mean-square signal estimation error. Theoretical expressions for probability of false alarm and probability of detection are derived for all the detectors, and the theoretical predictions are compared with simulation results. It is shown that the detection performance of an AVS array with a certain number of sensors is equal to or slightly better than that of a conventional acoustic pressure sensor array with thrice as many sensors.

Looking for an invisible Higgs signal at the LHC

While the recent discovery of a Higgs-like boson at the LHC is an extremely important and encouraging step towards the discovery of the complete Standard Model (SM), the current information on this state does not rule out possibility of beyond standard model (BSM) physics. In fact the current data can still accommodate reasonably large values of the branching fractions of the Higgs into a channel with `invisible' decay products, such a channel being also well motivated theoretically. In this study we revisit the possibility of detecting the Higgs in this invisible channel for both choices of the LHC energies, 8 and 14 TeV, for two production modes; vector boson fusion (VBF) and associated production (ZH). We perform a comprehensive collider analysis for all the above channels and project the reach of LHC to constrain the invisible decay branching fraction for both 8 and 14 TeV energies. For the ZH case we consider decays of the Z boson into a pair of leptons as well as a b (b) over bar pair. For the VBF channel the sensitivity is found to be more than 5 sigma for both the energies up to an invisible branching ratio (Br-inv) similar to 0.80, with luminosities similar to 20/30 fb(-1). The sensitivity is further extended to values of Br-inv similar to 0.25 for 300 fb(-1) at 14 TeV. However the reach is found to be more modest for the ZH mode with leptonic final state; with about 3.5 sigma for the planned luminosity at 8 TeV, reaching 8 sigma only for 14 TeV for 50 fb(-1). In spite of the much larger branching ratio (BR) of the Z into a b (b) over bar channel compared to the dilepton case, the former channel, can provide useful reach up to Br-inv greater than or similar to 0.75, only for the higher luminosity (300 fb(-1)) option using both jet-substructure and jet clustering methods. (C) 2013 Elsevier B.V. All rights reserved.

Photoacoustic and thermoacoustic signal characteristics study

Photoacoustic/thermoacoustic imaging is an emerging hybrid imaging modality combining optical/microwave imaging with ultrasound imaging. The photoacoustic/thermoacoustic signal generated are affected by the nature of excitation pulse waveform, pulse width, target object size, transducer size etc. In this study k-wave was used to simulate various configurations of excitation pulse, transducer types, and target object sizes and to see their effect on the photoacoustic/thermoacoustic signals. Numerical blood vessel phantom was also used to see the effect of various pulse waveform and excitation pulse width on the reconstructed images. This study will help in optimizing transducer design and reconstruction methods to obtain the superior reconstructed image.

Wide Voltage Input Receiver with Hysteresis Characteristic to Reduce Input Signal Noise Effect

In this paper, an input receiver with a hysteresis characteristic that can work at voltage levels between 0.9 V and 5 V is proposed. The input receiver can be used as a wide voltage range Schmitt trigger also. At the same time, reliable circuit operation is ensured. According to the research findings, this is the first time a wide voltage range Schmitt trigger is being reported. The proposed circuit is compared with previously reported input receivers, and it is shown that the circuit has better noise immunity. The proposed input receiver ends the need for a separate Schmitt trigger and input buffer. The frequency of operation is also higher than that of the previously reported receiver. The circuit is simulated using HSPICE at 035-mu m standard thin oxide technology. Monte Carlo analysis is conducted at different process conditions, showing that the proposed circuit works well for different process conditions at different voltage levels of operation. A noise impulse of (V-CC/2) magnitude is added to the input voltage to show that the receiver receives the correct logic level even in the presence of noise. Here, V-CC is the fixed voltage supply of 3.3 V.

On Computing Amplitude, Phase, and Frequency Modulations Using a Vector Interpretation of the Analytic Signal

The amplitude-modulation (AM) and phase-modulation (PM) of an amplitude-modulated frequency-modulated (AM-FM) signal are defined as the modulus and phase angle, respectively, of the analytic signal (AS). The FM is defined as the derivative of the PM. However, this standard definition results in a PM with jump discontinuities in cases when the AM index exceeds unity, resulting in an FM that contains impulses. We propose a new approach to define smooth AM, PM, and FM for the AS, where the PM is computed as the solution to an optimization problem based on a vector interpretation of the AS. Our approach is directly linked to the fractional Hilbert transform (FrHT) and leads to an eigenvalue problem. The resulting PM and AM are shown to be smooth, and in particular, the AM turns out to be bipolar. We show an equivalence of the eigenvalue formulation to the square of the AS, and arrive at a simple method to compute the smooth PM. Some examples on synthesized and real signals are provided to validate the theoretical calculations.

Noncoherent Integration for Signal Detection: Analysis Under Model Uncertainties

The performance of postdetection integration (PDI) techniques for the detection of Global Navigation Satellite Systems (GNSS) signals in the presence of uncertainties in frequency offsets, noise variance, and unknown data-bits is studied. It is shown that the conventional PDI techniques are generally not robust to uncertainty in the data-bits and/or the noise variance. Two new modified PDI techniques are proposed, and they are shown to be robust to these uncertainties. The receiver operating characteristics (ROC) and sample complexity performance of the PDI techniques in the presence of model uncertainties are analytically derived. It is shown that the proposed methods significantly outperform existing methods, and hence they could become increasingly important as the GNSS receivers attempt to push the envelope on the minimum signal-to-noise ratio (SNR) for reliable detection.

High-resolution restoration of 3D structures from widefield images with extreme low signal-to-noise-ratio

Four-dimensional fluorescence microscopy-which records 3D image information as a function of time-provides an unbiased way of tracking dynamic behavior of subcellular components in living samples and capturing key events in complex macromolecular processes. Unfortunately, the combination of phototoxicity and photobleaching can severely limit the density or duration of sampling, thereby limiting the biological information that can be obtained. Although widefield microscopy provides a very light-efficient way of imaging, obtaining high-quality reconstructions requires deconvolution to remove optical aberrations. Unfortunately, most deconvolution methods perform very poorly at low signal-to-noise ratios, thereby requiring moderate photon doses to obtain acceptable resolution. We present a unique deconvolution method that combines an entropy-based regularization function with kernels that can exploit general spatial characteristics of the fluorescence image to push the required dose to extreme low levels, resulting in an enabling technology for high-resolution in vivo biological imaging.