Event-triggered sampling using signal extrema for instantaneous amplitude and instantaneous frequency estimation

Event-triggered sampling (ETS) is a new approach towards efficient signal analysis. The goal of ETS need not be only signal reconstruction, but also direct estimation of desired information in the signal by skillful design of event. We show a promise of ETS approach towards better analysis of oscillatory non-stationary signals modeled by a time-varying sinusoid, when compared to existing uniform Nyquist-rate sampling based signal processing. We examine samples drawn using ETS, with events as zero-crossing (ZC), level-crossing (LC), and extrema, for additive in-band noise and jitter in detection instant. We find that extrema samples are robust, and also facilitate instantaneous amplitude (IA), and instantaneous frequency (IF) estimation in a time-varying sinusoid. The estimation is proposed solely using extrema samples, and a local polynomial regression based least-squares fitting approach. The proposed approach shows improvement, for noisy signals, over widely used analytic signal, energy separation, and ZC based approaches (which are based on uniform Nyquist-rate sampling based data-acquisition and processing). Further, extrema based ETS in general gives a sub-sampled representation (relative to Nyquistrate) of a time-varying sinusoid. For the same data-set size captured with extrema based ETS, and uniform sampling, the former gives much better IA and IF estimation. (C) 2015 Elsevier B.V. All rights reserved.

State Transition Based Embedding in Cepstrum Domain for Audio Copyright Protection

In this paper, we propose a new state transition based embedding (STBE) technique for audio watermarking with high fidelity. Furthermore, we propose a new correlation based encoding (CBE) scheme for binary logo image in order to enhance the payload capacity. The result of CBE is also compared with standard run-length encoding (RLE) compression and Huffman schemes. Most of the watermarking algorithms are based on modulating selected transform domain feature of an audio segment in order to embed given watermark bit. In the proposed STBE method instead of modulating feature of each and every segment to embed data, our aim is to retain the default value of this feature for most of the segments. Thus, a high quality of watermarked audio is maintained. Here, the difference between the mean values (Mdiff) of insignificant complex cepstrum transform (CCT) coefficients of down-sampled subsets is selected as a robust feature for embedding. Mdiff values of the frames are changed only when certain conditions are met. Hence, almost 50% of the times, segments are not changed and still STBE can convey watermark information at receiver side. STBE also exhibits a partial restoration feature by which the watermarked audio can be restored partially after extraction of the watermark at detector side. The psychoacoustic model analysis showed that the noise-masking ratio (NMR) of our system is less than -10dB. As amplitude scaling in time domain does not affect selected insignificant CCT coefficients, strong invariance towards amplitude scaling attacks is also proved theoretically. Experimental results reveal that the proposed watermarking scheme maintains high audio quality and are simultaneously robust to general attacks like MP3 compression, amplitude scaling, additive noise, re-quantization, etc.

A Few Case Studies on the Correlation of Particle Network and Its Stability on the Ionic Conductivity of Solid-Liquid Composite Electrolytes

We discuss here the crucial role of the particle network and its stability on the long-range ion transport in solid liquid composite electrolytes. The solid liquid composite electrolytes chosen for the study here comprise nanometer sized silica (SiO2) particles having various surface chemical functionalities dispersed in nonaqueous lithium salt solutions, viz, lithium perchlorate (LiClO4) in two different polyethylene glycol based solvents. These systems constitute representative examples of an independent class of soft matter electrolytes known as ``soggy sand'' electrolytes, which have tremendous potential in diverse electrochemical devices. The oxide additive acts as a heterogeneous dopant creating free charge carriers and enhancing the local ion transport. For long-range transport, however, a stable spanning particle network is needed. Systematic experimental investigations here reveal that the spatial and time dependent characteristics of the particle network in the liquid solution are nontrivial. The network characteristics are predominantly determined by the chemical makeup of the electrolyte components and the chemical interactions between them. It is noteworthy that in this study the steady state macroscopic ionic conductivity and viscosity of the solid liquid composite electrolyte are observed to be greatly determined by the additive oxide surface chemical functionality, solvent chemical composition, and solvent dielectric constant.

An Unbiased Risk Estimator for Multiplicative Noise - Application to 1-D Signal Denoising

The effect of multiplicative noise on a signal when compared with that of additive noise is very large. In this paper, we address the problem of suppressing multiplicative noise in one-dimensional signals. To deal with signals that are corrupted with multiplicative noise, we propose a denoising algorithm based on minimization of an unbiased estimator (MURE) of meansquare error (MSE). We derive an expression for an unbiased estimate of the MSE. The proposed denoising is carried out in wavelet domain (soft thresholding) by considering time-domain MURE. The parameters of thresholding function are obtained by minimizing the unbiased estimator MURE. We show that the parameters for optimal MURE are very close to the optimal parameters considering the oracle MSE. Experiments show that the SNR improvement for the proposed denoising algorithm is competitive with a state-of-the-art method.

In Situ Crystallographic Probing on Ameliorating Effect of Sulfide Additives and Carbon Grafting in Iron Electrodes

Beneficial effects of carbon grafting into the iron active material for rechargeable alkaline-iron-electrodes with and without Bi2S3 additive is probed by in situ X-ray diffraction in conjunction with Extended X-ray Absorption Fine Structure (EXAFS) and electrochemistry. EXAFS data unravel that the composition of pristine active material (PAM) for iron electrodes comprises 87% of magnetite and 13% of alpha-iron while carbon-grafted active material comprises 60% of magnetite and 40% of alpha-iron. In situ XRD patterns are recorded using a specially designed electrochemical cell. XRD data reflect that magnetite present in PAM iron electrode, without bismuth sulfide additive, is not reduced during charging while PAM iron electrode with bismuth sulfide additive is partially reduced to alpha-Fe/Fe(OH)(2). Interestingly, carbon-grafted-iron electrodes with bismuth sulfide exhibit complete conversion of active material to alpha-Fe/Fe(OH)2. The ameliorating effect of carbon grafting is substantiated by kinetic parameters obtained from steady-state potentiostatic polarization and Tafel plots. The mechanism for iron-electrode charge - discharge reactions are discussed in the light of the potential - pH diagrams for Fe - H2O, S - H2O and FeSads - H2O systems and it is surmised that carbon grafting into iron active material promotes its electrochemical utilization. (C) The Author(s) 2015. Published by ECS. All rights reserved.

Effect of combined treatment with zoledronic acid and propranolol on mechanical strength in an rat model of disuse osteoporosis

Objectives: A model that uses right hind-limb unloading of rats is used to study the consequences of skeletal unloading during various conditions like space flights and prolonged bed rest in elderly. This study was aimed to investigate the additive effects of antiresorptive agent zoledronic acid (ZOL), alone and in combination with propranolol (PRO) in a rat model of disuse osteoporosis. Methods: In the present study, 3-month-old male Wistar rats had their right hind-limb immobilized (RHLI) for 10 weeks to induce osteopenia, then were randomized into four groups: 1-RHLI positive control, 2-RHLI plus ZOL (50 mu g/kg, i.v. single dose), 3-RHLI plus PRO (0.1 mg/kg, s.c. 5 days per week), 4-RHLI plus PRO (0.1 mg/kg, s.c. 5 days per week) plus ZOL (50 mu g/kg, i.v. single dose) for another 10 weeks. One group of non-immobilized rats was used as negative control. At the end of treatment, the femurs were removed and tested for bone porosity, bone mechanical properties, and bone dry and ash weight. Results: With respect to improvement in the mechanical strength of the femoral mid-shaft, the combination treatment with ZOL plus PRO was more effective than ZOL or PRO monotherapy. Moreover, combination therapy using ZOL plus PRO was more effective in improving dry bone weight and preserved the cortical bone porosity better than monotherapy using ZOL or PRO in right hind-limb immobilized rats. Conclusions: These data suggest that this combined treatment with ZOL plus PRO should be recommended for the treatment of disuse osteoporosis. (C) 2014 Elsevier Editora Ltda. All rights reserved.

As-You-Go Deployment of a 2-Connected Wireless Relay Network for Sensor-Sink Interconnection

A person walks along a line (which could be an idealisation of a forest trail, for example), placing relays as he walks, in order to create a multihop network for connecting a sensor at a point along the line to a sink at the start of the line. The potential placement points are equally spaced along the line, and at each such location the decision to place or not to place a relay is based on link quality measurements to the previously placed relays. The location of the sensor is unknown apriori, and is discovered as the deployment agent walks. In this paper, we extend our earlier work on this class of problems to include the objective of achieving a 2-connected multihop network. We propose a network cost objective that is additive over the deployed relays, and accounts for possible alternate routing over the multiple available paths. As in our earlier work, the problem is formulated as a Markov decision process. Placement algorithms are obtained for two source location models, which yield a discounted cost MDP and an average cost MDP. In each case we obtain structural results for an optimal policy, and perform a numerical study that provides insights into the advantages and disadvantages of multi-connectivity. We validate the results obtained from numerical study experimentally in a forest-like environment.

Event-triggered Sampling and Reconstruction of Sparse Real-valued Trigonometric Polynomials

We propose data acquisition from continuous-time signals belonging to the class of real-valued trigonometric polynomials using an event-triggered sampling paradigm. The sampling schemes proposed are: level crossing (LC), close to extrema LC, and extrema sampling. Analysis of robustness of these schemes to jitter, and bandpass additive gaussian noise is presented. In general these sampling schemes will result in non-uniformly spaced sample instants. We address the issue of signal reconstruction from the acquired data-set by imposing structure of sparsity on the signal model to circumvent the problem of gap and density constraints. The recovery performance is contrasted amongst the various schemes and with random sampling scheme. In the proposed approach, both sampling and reconstruction are non-linear operations, and in contrast to random sampling methodologies proposed in compressive sensing these techniques may be implemented in practice with low-power circuitry.

SPEECH ENHANCEMENT USING DISCRIMINATIVE RANDOM FIELDS

Speech enhancement in stationary noise is addressed using the ideal channel selection framework. In order to estimate the binary mask, we propose to classify each time-frequency (T-F) bin of the noisy signal as speech or noise using Discriminative Random Fields (DRF). The DRF function contains two terms - an enhancement function and a smoothing term. On each T-F bin, we propose to use an enhancement function based on likelihood ratio test for speech presence, while Ising model is used as smoothing function for spectro-temporal continuity in the estimated binary mask. The effect of the smoothing function over successive iterations is found to reduce musical noise as opposed to using only enhancement function. The binary mask is inferred from the noisy signal using Iterated Conditional Modes (ICM) algorithm. Sentences from NOIZEUS corpus are evaluated from 0 dB to 15 dB Signal to Noise Ratio (SNR) in 4 kinds of additive noise settings: additive white Gaussian noise, car noise, street noise and pink noise. The reconstructed speech using the proposed technique is evaluated in terms of average segmental SNR, Perceptual Evaluation of Speech Quality (PESQ) and Mean opinion Score (MOS).

Transition metal-free Minisci reaction promoted by NCS, and TBHP: acylation of heteroarenes

A method for acylation for heteroarenes under metal-free conditions has been described using NCS as an additive and TBHP as an oxidant. This method has been successfully employed in acylation of a variety of aldehyde with heteroarenes. The application of the method has been illustrated in synthesizing isoquinoline derived natural products. This strategy provides an efficient, mild and inexpensive method for acylation of heteroarenes. (C) 2015 Elsevier Ltd. All rights reserved.

Pd-Catalyzed Hydroborylation of Alkynes: A Ligand Controlled Regioselectivity Switch for the Synthesis of alpha- or beta-Vinylboronates

A ligand controlled selective hydroborylation of alkynes to alpha- or beta-vinylboronates has been developed using a Pd catalyst. The high alpha-selectivity displayed by this reaction can be switched to furnish beta-vinylboronates by altering the ligand from a trialkylphosphine to N-heterocyclic carbene. A variety of terminal alkynes are shown to furnish the corresponding alpha- or beta-vinylboronates in good to excellent selectivity and yield. The mechanistic studies suggest that the solvent is the proton source and bromobenzene functions as an important additive in driving this reaction forward.

Pd-Catalyzed Hydroborylation of Alkynes: A Ligand Controlled Regioselectivity Switch for the Synthesis of alpha- or beta-Vinylboronates

A ligand controlled selective hydroborylation of alkynes to alpha- or beta-vinylboronates has been developed using a Pd catalyst. The high alpha-selectivity displayed by this reaction can be switched to furnish beta-vinylboronates by altering the ligand from a trialkylphosphine to N-heterocyclic carbene. A variety of terminal alkynes are shown to furnish the corresponding alpha- or beta-vinylboronates in good to excellent selectivity and yield. The mechanistic studies suggest that the solvent is the proton source and bromobenzene functions as an important additive in driving this reaction forward.

Strength reliability and in vitro degradation of three-dimensional powder printed strontium-substituted magnesium phosphate scaffolds

Strontium ions (Sr2+) are known to prevent osteoporosis and also encourage bone formation. Such twin requirements have motivated researchers to develop Sr-substituted biomaterials for orthopaedic applications. The present study demonstrates a new concept of developing Sr-substituted Mg-3(PO4)(2) - based biodegradable scaffolds. In particular, this work reports the fabrication, mechanical properties with an emphasis on strength reliability as well as in vitro degradation of highly biodegradable strontium-incorporated magnesium phosphate cements. These implantable scaffolds were fabricated using three-dimensional powder printing, followed by high temperature sintering and/or chemical conversion, a technique adaptable to develop patient-specific implants. A moderate combination of strength properties of 36.7 MPa (compression), 242 MPa (bending) and 10.7 MPa (tension) were measured. A reasonably modest Weibull modulus of up to 8.8 was recorded after uniaxial compression or diametral tensile tests on 3D printed scaffolds. A comparison among scaffolds with varying compositions or among sintered or chemically hardened scaffolds reveals that the strength reliability is not compromised in Sr-substituted scaffolds compared to baseline Mg-3(PO4)(2). The micro-computed tomography analysis reveals the presence of highly interconnected porous architecture in three-dimension with lognormal pore size distribution having median in the range of 17.74-26.29 mu m for the investigated scaffolds. The results of extensive in vitro ion release study revealed passive degradation with a reduced Mg2+ release and slow but sustained release of Sr2+ from strontium-substituted magnesium phosphate scaffolds. Taken together, the present study unequivocally illustrates that the newly designed Sr-substituted magnesium phosphate scaffolds with good strength reliability could be used for biomedical applications requiring consistent Sr2+-release, while the scaffold degrades in physiological medium. Statement of significance The study investigates the additive manufacturing of scaffolds based on different strontium-substituted magnesium phosphate bone cements by means of three-dimensional powder printing technique (3DPP). Magnesium phosphates were chosen due to their higher biodegradability compared to calcium phosphates, which is due to both a higher solubility as well as the absence of phase changes (to low soluble hydroxyapatite) in vivo. Since strontium ions are known to promote bone formation by stimulating osteoblast growth, we aimed to establish such a highly degradable magnesium phosphate ceramic with an enhanced bioactivity for new bone ingrowth. After post-processing, mechanical strengths of up to 36.7 MPa (compression), 24.2 MPa (bending) and 10.7 MPa (tension) could be achieved. Simultaneously, the failure reliability of those bioceramic implant materials, measured by Weibull modulus calculations, were in the range of 4.3-8.8. Passive dissolution studies in vitro proved an ion release of Mg2+ and PO43- as well as Sr2+, which is fundamental for in vivo degradation and a bone growth promoting effect. In our opinion, this work broadens the range of bioceramic bone replacement materials suitable for additive manufacturing processing. The high biodegradability of MPC ceramics together with the anticipated promoting effect on osseointegration opens up the way for a patient-specific treatment with the prospect of a fast and complete healing of bone fractures. (C) 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Characterization of silver-kaolinite (AgK): an adsorbent for long-lived I-129 species

Bentonite is a preferred buffer and backfill material for deep geological disposal of high-level nuclear waste (HLW). Bentonite does not retain anions by virtue of its negatively charged basal surface. Imparting anion retention ability to bentonite is important to enable the expansive clay to retain long-lived I-129 (iodine-129; half-life = 16 million years) species that may escape from the HLW geological repository. Silver-kaolinite (AgK) material is prepared as an additive to improve the iodide retention capacity of bentonite. The AgK is prepared by heating kaolinite-silver nitrate mix at 400 degrees C to study the kaolinite influence on the transition metal ion when reacting at its dehydroxylation temperature. Thermo gravimetric-Evolved Gas Detection analysis, X-ray diffraction analysis, X-ray photo electron spectroscopy and electron probe micro analysis indicated that silver occurs as AgO/Ag2O surface coating on thermally reacting kaolinite with silver nitrate at 400 degrees C.

l(1)-K-SVD: A robust dictionary learning algorithm with simultaneous update

We develop a new dictionary learning algorithm called the l(1)-K-svp, by minimizing the l(1) distortion on the data term. The proposed formulation corresponds to maximum a posteriori estimation assuming a Laplacian prior on the coefficient matrix and additive noise, and is, in general, robust to non-Gaussian noise. The l(1) distortion is minimized by employing the iteratively reweighted least-squares algorithm. The dictionary atoms and the corresponding sparse coefficients are simultaneously estimated in the dictionary update step. Experimental results show that l(1)-K-SVD results in noise-robustness, faster convergence, and higher atom recovery rate than the method of optimal directions, K-SVD, and the robust dictionary learning algorithm (RDL), in Gaussian as well as non-Gaussian noise. For a fixed value of sparsity, number of dictionary atoms, and data dimension, l(1)-K-SVD outperforms K-SVD and RDL on small training sets. We also consider the generalized l(p), 0 < p < 1, data metric to tackle heavy-tailed/impulsive noise. In an image denoising application, l(1)-K-SVD was found to result in higher peak signal-to-noise ratio (PSNR) over K-SVD for Laplacian noise. The structural similarity index increases by 0.1 for low input PSNR, which is significant and demonstrates the efficacy of the proposed method. (C) 2015 Elsevier B.V. All rights reserved.