Approximate Nearest Neighbour Field based Optic Disk Detection

Approximate Nearest Neighbour Field maps are commonly used by computer vision and graphics community to deal with problems like image completion, retargetting, denoising, etc. In this paper, we extend the scope of usage of ANNF maps to medical image analysis, more specifically to optic disk detection in retinal images. In the analysis of retinal images, optic disk detection plays an important role since it simplifies the segmentation of optic disk and other retinal structures. The proposed approach uses FeatureMatch, an ANNF algorithm, to find the correspondence between a chosen optic disk reference image and any given query image. This correspondence provides a distribution of patches in the query image that are closest to patches in the reference image. The likelihood map obtained from the distribution of patches in query image is used for optic disk detection. The proposed approach is evaluated on five publicly available DIARETDB0, DIARETDB1, DRIVE, STARE and MESSIDOR databases, with total of 1540 images. We show, experimentally, that our proposed approach achieves an average detection accuracy of 99% and an average computation time of 0.2 s per image. (C) 2013 Elsevier Ltd. All rights reserved.

Detection of the closure-burst transitions of stops and affricates in continuous speech using the plosion index

Automatic and accurate detection of the closure-burst transition events of stops and affricates serves many applications in speech processing. A temporal measure named the plosion index is proposed to detect such events, which are characterized by an abrupt increase in energy. Using the maxima of the pitch-synchronous normalized cross correlation as an additional temporal feature, a rule-based algorithm is designed that aims at selecting only those events associated with the closure-burst transitions of stops and affricates. The performance of the algorithm, characterized by receiver operating characteristic curves and temporal accuracy, is evaluated using the labeled closure-burst transitions of stops and affricates of the entire TIMIT test and training databases. The robustness of the algorithm is studied with respect to global white and babble noise as well as local noise using the TIMIT test set and on telephone quality speech using the NTIMIT test set. For these experiments, the proposed algorithm, which does not require explicit statistical training and is based on two one-dimensional temporal measures, gives a performance comparable to or better than the state-of-the-art methods. In addition, to test the scalability, the algorithm is applied on the Buckeye conversational speech corpus and databases of two Indian languages. (C) 2014 Acoustical Society of America.

Selective and Efficient Detection of Nitro-Aromatic Explosives in Multiple Media including Water, Micelles, Organogel, and Solid Support

Selective detection of nitro-aromatic compounds (NACs) at nanomolar concentration is achieved for the first time in multiple media including water, micelles or in organogels as well as using test strips. Mechanism of interaction of NACs with highly fluorescent p-phenylenevinylene-based molecules has been described as the electron transfer phenomenon from the electron-rich chromophoric probe to the electron deficient NACs. The selectivity in sensing is guided by the pK(a) of the probes as well as the NACs under consideration. TNP-induced selective gel-to-sol transition in THF medium is also observed through the reorganization of molecular self-assembly and the portable test trips are made successfully for rapid on-site detection purpose.

Filling-in Void and Sparse Regions in Protein Sequence Space by Protein-Like Artificial Sequences Enables Remarkable Enhancement in Remote Homology Detection Capability

Protein functional annotation relies on the identification of accurate relationships, sequence divergence being a key factor. This is especially evident when distant protein relationships are demonstrated only with three-dimensional structures. To address this challenge, we describe a computational approach to purposefully bridge gaps between related protein families through directed design of protein-like ``linker'' sequences. For this, we represented SCOP domain families, integrated with sequence homologues, as multiple profiles and performed HMM-HMM alignments between related domain families. Where convincing alignments were achieved, we applied a roulette wheel-based method to design 3,611,010 protein-like sequences corresponding to 374 SCOP folds. To analyze their ability to link proteins in homology searches, we used 3024 queries to search two databases, one containing only natural sequences and another one additionally containing designed sequences. Our results showed that augmented database searches showed up to 30% improvement in fold coverage for over 74% of the folds, with 52 folds achieving all theoretically possible connections. Although sequences could not be designed between some families, the availability of designed sequences between other families within the fold established the sequence continuum to demonstrate 373 difficult relationships. Ultimately, as a practical and realistic extension, we demonstrate that such protein-like sequences can be ``plugged-into'' routine and generic sequence database searches to empower not only remote homology detection but also fold recognition. Our richly statistically supported findings show that complementary searches in both databases will increase the effectiveness of sequence-based searches in recognizing all homologues sharing a common fold. (C) 2013 Elsevier Ltd. All rights reserved.

An Efficient Probe for Rapid Detection of Cyanide in Water at Parts per Billion Levels and Naked-Eye Detection of Endogenous Cyanide

A new molecular probe based on an oxidized bis-indolyl skeleton has been developed for rapid and sensitive visual detection of cyanide ions in water and also for the detection of endogenously bound cyanide. The probe allows the naked-eye detection of cyanide ions in water with a visual color change from red to yellow ((max)=80nm) with the immediate addition of the probe. It shows high selectivity towards the cyanide ion without any interference from other anions. The detection of cyanide by the probe is ratiometric, thus making the detection quantitative. A Michael-type addition reaction of the probe with the cyanide ion takes place during this chemodosimetric process. In water, the detection limit was found to be at the parts per million level, which improved drastically when a neutral micellar medium was employed, and it showed a parts-per-billion-level detection, which is even 25-fold lower than the permitted limits of cyanide in water. The probe could also efficiently detect the endogenously bound cyanide in cassava (a staple food) with a clear visual color change without requiring any sample pretreatment and/or any special reaction conditions such as pH or temperature. Thus the probe could serve as a practical naked-eye probe for in-field experiments without requiring any sophisticated instruments.

Threshold-Independent QRS Detection Using the Dynamic Plosion Index

Detection of QRS serves as a first step in many automated ECG analysis techniques. Motivated by the strong similarities between the signal structures of an ECG signal and the integrated linear prediction residual (ILPR) of voiced speech, an algorithm proposed earlier for epoch detection from ILPR is extended to the problem of QRS detection. The ECG signal is pre-processed by high-pass filtering to remove the baseline wandering and by half-wave rectification to reduce the ambiguities. The initial estimates of the QRS are iteratively obtained using a non-linear temporal feature, named the dynamic plosion index suitable for detection of transients in a signal. These estimates are further refined to obtain a higher temporal accuracy. Unlike most of the high performance algorithms, this technique does not make use of any threshold or differencing operation. The proposed algorithm is validated on the MIT-BIH database using the standard metrics and its performance is found to be comparable to the state-of-the-art algorithms, despite its threshold independence and simple decision logic.

Lattice Reduction Aided Detection in Large-MIMO Systems

Lattice reduction (LR) aided detection algorithms are known to achieve the same diversity order as that of maximum-likelihood (ML) detection at low complexity. However, they suffer SNR loss compared to ML performance. The SNR loss is mainly due to imperfect orthogonalization and imperfect nearest neighbor quantization. In this paper, we propose an improved LR-aided (ILR) detection algorithm, where we specifically target to reduce the effects of both imperfect orthogonalization and imperfect nearest neighbor quantization. The proposed ILR detection algorithm is shown to achieve near-ML performance in large-MIMO systems and outperform other LR-aided detection algorithms in the literature. Specifically, the SNR loss incurred by the proposed ILR algorithm compared to ML performance is just 0.1 dB for 4-QAM and < 0.5 dB for 16-QAM in 16 x 16 V-BLAST MIMO system. This performance is superior compared to those of other LR-aided detection algorithms, whose SNR losses are in the 2 dB to 9 dB range.

Calibration Curve with Improved Limit of Detection for Cadmium in Soil: An Approach to Minimize the Matrix Effect in Laser-Induced Breakdown Spectroscopic Analysis

The present article describes a working or combined calibration curve in laser-induced breakdown spectroscopic analysis, which is the cumulative result of the calibration curves obtained from neutral and singly ionized atomic emission spectral lines. This working calibration curve reduces the effect of change in matrix between different zone soils and certified soil samples because it includes both the species' (neutral and singly ionized) concentration of the element of interest. The limit of detection using a working calibration curve is found better as compared to its constituent calibration curves (i.e., individual calibration curves). The quantitative results obtained using the working calibration curve is in better agreement with the result of inductively coupled plasma-atomic emission spectroscopy as compared to the result obtained using its constituent calibration curves.

PocketMatch (version 2.0): A parallel algorithm for the detection of structural similarities between protein ligand binding-sites

Knowledge of protein-ligand interactions is essential to understand several biological processes and important for applications ranging from understanding protein function to drug discovery and protein engineering. Here, we describe an algorithm for the comparison of three-dimensional ligand-binding sites in protein structures. A previously described algorithm, PocketMatch (version 1.0) is optimised, expanded, and MPI-enabled for parallel execution. PocketMatch (version 2.0) rapidly quantifies binding-site similarity based on structural descriptors such as residue nature and interatomic distances. Atomic-scale alignments may also be obtained from amino acid residue pairings generated. It allows an end-user to compute database-wide, all-to-all comparisons in a matter of hours. The use of our algorithm on a sample dataset, performance-analysis, and annotated source code is also included.

Voltammetric detection of arsenic on a bismuth modified exfoliated graphite electrode

We present the application of a bismuth modified exfoliated graphite electrode in the detection of arsenic in water. Bismuth film was electrodeposited onto an exfoliated graphite (EG) electrode at a potential of -600 mV. The modification of EG resulted in an increase in the electroactive surface area of the electrode and consequently peak current enhancement in Ru(NH3)(6)(2+/13+) redox probe. Square wave anodic stripping voltammetry was performed with the modified electrode (EG-Bi) in As (III) solutions at the optimum conditions of pH 6, deposition potential of -600 mV and pre-concentration time of 180s. The EG-Bi was able to detect As (III) to the limit of 5 mu g L-1 and was not susceptible to many interfering cations except Cu (II). The EG-Bi is low cost and easy to prepare. (C) 2013 Elsevier Ltd. All rights reserved.

Detection of Target DNA using Photo-Reactive Protoporphyrin Moeity on a Nanocomposite Substrate

Detection of pathogens from infected biological samples through conventional process involves cell lysis and purification. The main objective of this work is to minimize the time and sample loss, as well as to increase the efficiency of detection of biomolecules. Electrical lysis of medical sample is performed in a closed microfluidic channel in a single integrated platform where the downstream analysis of the sample is possible. The device functions involve, in a sequence, flow of lysate from lysis chamber passed through a thermal denaturation counter where dsDNA is denatured to ssDNA, which is controlled by heater unit. A functionalized binding chamber of ssDNA is prepared by using ZnO nanorods as the matrix and functionalized with bifunctional carboxylic acid, 16-(2-pyridyldithiol) hexadecanoic acid (PDHA) which is further attached to a linker molecule 1-ethyl-3-(3-dimethylaminopropyl) (EDC). Linker moeity is then covalently bound to photoreactive protoporphyrin (PPP) molecule. The photolabile molecule protoporphyrin interacts with -NH2 labeled single stranded DNA (ssDNA) which thus acts as a probe to detect complimentary ssDNA from target organisms. Thereafter the bound DNA with protoporphyrin is exposed to an LED of particular wavelength for a definite period of time and DNA was eluted and analyzed. UV/Vis spectroscopic analysis at 260/280 nm wavelength confirms the purity and peak at 260 nm is reconfirmed for the elution of target DNA. Quantitative and qualitative data obtained from the current experiments show highly selective detection of biomolecule such as DNA which have large number of future applications in Point-of-Care devices.

Titania nanotube-modified screen printed carbon electrodes enhance the sensitivity in the electrochemical detection of proteins

The use of titania nanotubes (TiO2-NT) as the working electrode provides a substantial improvement in the electrochemical detection of proteins. A biosensor designed using this strategy provided a robust method to detect protein samples at very low concentrations (C-protein ca 1 ng/mu l). Reproducible measurements on protein samples at this concentration (I-p,I-a of 80 +/- 1.2 mu A) could be achieved using a sample volume of ca 30 mu l. We demonstrate the feasibility of this strategy for the accurate detection of penicillin binding protein, PBP2a, a marker for methicillin resistant Staphylococcus aureus (MRSA). The selectivity and efficiency of this sensor were also validated using other diverse protein preparations such as a recombinant protein tyrosine phosphatase (PTP10D) and bovine serum albumin (BSA). This electrochemical method also presents a substantial improvement in the time taken (few minutes) when compared to conventional enzyme-linked immunosorbent assay (ELISA) protocols. It is envisaged that this sensor could substantially aid in the rapid diagnosis of bacterial infections in resource strapped environments. (C) 2014 Elsevier B.V. All rights reserved.

Joint Approximately Sparse Channel Estimation and Data Detection in OFDM Systems Using Sparse Bayesian Learning

It is well known that the impulse response of a wide-band wireless channel is approximately sparse, in the sense that it has a small number of significant components relative to the channel delay spread. In this paper, we consider the estimation of the unknown channel coefficients and its support in OFDM systems using a sparse Bayesian learning (SBL) framework for exact inference. In a quasi-static, block-fading scenario, we employ the SBL algorithm for channel estimation and propose a joint SBL (J-SBL) and a low-complexity recursive J-SBL algorithm for joint channel estimation and data detection. In a time-varying scenario, we use a first-order autoregressive model for the wireless channel and propose a novel, recursive, low-complexity Kalman filtering-based SBL (KSBL) algorithm for channel estimation. We generalize the KSBL algorithm to obtain the recursive joint KSBL algorithm that performs joint channel estimation and data detection. Our algorithms can efficiently recover a group of approximately sparse vectors even when the measurement matrix is partially unknown due to the presence of unknown data symbols. Moreover, the algorithms can fully exploit the correlation structure in the multiple measurements. Monte Carlo simulations illustrate the efficacy of the proposed techniques in terms of the mean-square error and bit error rate performance.

A Probe for the Selective and Parts-per-Billion-Level Detection of Copper(II) and Mercury(II) using a Micellar Medium and Its Utility in Cell Imaging

A novel colorimetric probe 1 based on the picolyl moiety has been designed and synthesized. Probe 1 is composed of a pyrene and a bispicolyl amine (BPA) unit, in which the BPA moiety acts as a binding unit and the binding phenomenon is sensed from the changes in the signaling subunit. The probe detects Cu2+ specifically in water and both Cu2+ and Hg2+ efficiently in neutral Brij-58 micellar media. The probe shows a color change visible to the naked eye upon addition of metal ions. Notably, in a micellar medium, probe 1 can detect both the Cu2+ and Hg2+ ions even at parts-per-billion levels. Furthermore, the probe shows ratiometric detection of both the metal ions making the sensing quantitative. The two metal ions could be discriminated both visibly under a UV lamp and with the use of fluorescence spectroscopy. The probe could be also used in biological cell lines for the detection of both Hg2+ and Cu2+ ions.

Spectrum sensing using distributed sequential detection via noisy reporting MAC

This paper considers cooperative spectrum sensing algorithms for Cognitive Radios which focus on reducing the number of samples to make a reliable detection. We propose algorithms based on decentralized sequential hypothesis testing in which the Cognitive Radios sequentially collect the observations, make local decisions and send them to the fusion center for further processing to make a final decision on spectrum usage. The reporting channel between the Cognitive Radios and the fusion center is assumed more realistically as a Multiple Access Channel (MAC) with receiver noise. Furthermore the communication for reporting is limited, thereby reducing the communication cost. We start with an algorithm where the fusion center uses an SPRT-like (Sequential Probability Ratio Test) procedure and theoretically analyze its performance. Asymptotically, its performance is close to the optimal centralized test without fusion center noise. We further modify this algorithm to improve its performance at practical operating points. Later we generalize these algorithms to handle uncertainties in SNR and fading. (C) 2014 Elsevier B.V. All rights reserved.