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.

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.

Highly sensitive and rapid detection of acetylcholine using an ITO plate modified with platinum-graphene nanoparticles

Determining the concentrations of acetylcholine (ACh) and choline (Ch) is clinically important. ACh is a neurotransmitter that acts as a key link in the communication between neurons in the spinal cord and in nerve skeletal junctions in vertebrates, and plays an important role in transmitting signals in the brain. A bienzymatic sensor for the detection of ACh was prepared by co-immobilizing choline oxidase (ChO) and acetylcholinesterase (AChE) on graphene matrix/platinum nanoparticles, and then electrodepositing them on an ITO-coated glass plate. Graphene nanoparticles were decorated with platinum nanoparticles and were electrodeposited on a modified ITO-coated glass plate to form a modified electrode. The modified electrode was characterized by scanning electron microscopy (SEM), cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) studies. The optimum response of the enzyme electrode was obtained at pH 7.0 and 35 degrees C. The response time of this ACh-sensing system was shown to be 4 s. The linear range of responses to ACh was 0.005-700 mu M. This biosensor exhibits excellent anti-interferential abilities and good stability, retaining 50% of its original current even after 4 months. It has been applied for the detection of ACh levels in human serum samples.

Polyfunctional Lewis Acids: Intriguing Solid-State Structure and Selective Detection and Discrimination of Nitroaromatic Explosives

Synthesis and crystal structures of three porphyrin-based polyfunctional Lewis acids 1-3 are reported. Intermolecular HgClHgCl (linear and -type) interactions in the solid state of the peripherally ArHgCl-decorated compound 3 lead to a fascinating 3D supramolecular architecture. Compound3 shows a selective fluorescence quenching response to picric acid and discriminates other nitroaromatic-based explosives. For the first time, an electron-deficient polyfunctional Lewis acid is shown to be useful for the selective detection and discrimination of nitroaromatic explosives. The Stern-Volmer quenching constant and detection limits of compound3 for picric acid are the best among the reported small-molecular receptors for nitroaromatic explosives. The electronic structure, Lewis acidity, and selective sensing characteristics of 3 are well corroborated by DFT calculations.

Boron and Nitrogen Co-doped Carbon Nanoparticles as Photoluminescent Probes for Selective and Sensitive Detection of Picric Acid

Here, we report the synthesis of boron and nitrogen Co-doped carbon nanoparticles (BN-CNPs) by a hydrothermal method using sucrose, boric acid, and urea as the precursors. The BN-CNPs show excellent photoluminescence with a quantum yield of similar to 14.2% in aqueous solution and can be used as photoluminescent probes for selective and sensitive detection of picric acid (PA). PA quenches the photoluminescence signal remarkably, while other explosives cause a little quenching confirming the high selectivity of BN-CNPs. The sensitivity toward PA sensing is high at pH 7 and increases with temperature. The detection limit as well as the sensitivity are shown to improve by adding NaCl to the PA. The low detection limit can be as low as 10 nM at room temperature and pH 7, which indicates the BN-CNPs are superior as compared to other luminescent probes reported in the literature.

Joint Channel Estimation and Data Detection in MIMO-OFDM Systems: A Sparse Bayesian Learning Approach

The impulse response of wireless channels between the N-t transmit and N-r receive antennas of a MIMO-OFDM system are group approximately sparse (ga-sparse), i.e., NtNt the channels have a small number of significant paths relative to the channel delay spread and the time-lags of the significant paths between transmit and receive antenna pairs coincide. Often, wireless channels are also group approximately cluster-sparse (gac-sparse), i.e., every ga-sparse channel consists of clusters, where a few clusters have all strong components while most clusters have all weak components. In this paper, we cast the problem of estimating the ga-sparse and gac-sparse block-fading and time-varying channels in the sparse Bayesian learning (SBL) framework and propose a bouquet of novel algorithms for pilot-based channel estimation, and joint channel estimation and data detection, in MIMO-OFDM systems. The proposed algorithms are capable of estimating the sparse wireless channels even when the measurement matrix is only partially known. Further, we employ a first-order autoregressive modeling of the temporal variation of the ga-sparse and gac-sparse channels and propose a recursive Kalman filtering and smoothing (KFS) technique for joint channel estimation, tracking, and data detection. We also propose novel, parallel-implementation based, low-complexity techniques for estimating gac-sparse channels. Monte Carlo simulations illustrate the benefit of exploiting the gac-sparse structure in the wireless channel in terms of the mean square error (MSE) and coded bit error rate (BER) performance.

Soluble Angiopoietin Receptor Tie-2 In Patients With Acute Myocardial Infarction And Its Detection By Optical Protein-Chip

The Tie-2 receptor has been shown to play a role in angiogenesis in atherosclerosis. The conventional method assaying the level of soluble Tie-2 (sTie-2) was ELISA. However, this method has some disadvantages. The aims of this research are to establish a more simple detection method, the optical protein-chip based on imaging ellipsomtry (OPC-IE) applying to Tie-2 assay. The sTie-2 biosensor surface on silicon wafer was prepared first, and then serum levels of sTie-2 in 38 patients with AMI were measured on admission (day 1), day 2, day 3 and day 7 after onset of chest pain and 41 healthy controls by ELISA and OPC-IE in parallel. Median level of sTie-2 increased significantly in the AMI patients when compared with the controls. Statistics showed there was a significant correlation in sTie-2 results between the two methods (r=0.923, P0.01). The result of this study showed that the level of sTie-2 increased in AMI, and OPC-IE assay was a fast, reliable, and convenient technique to measure sTie-2 in serum.

Fiber-optic integration and efficient detection schemes for optomechanical resonators

With the advent of the laser in the year 1960, the field of optics experienced a renaissance from what was considered to be a dull, solved subject to an active area of development, with applications and discoveries which are yet to be exhausted 55 years later. Light is now nearly ubiquitous not only in cutting-edge research in physics, chemistry, and biology, but also in modern technology and infrastructure. One quality of light, that of the imparted radiation pressure force upon reflection from an object, has attracted intense interest from researchers seeking to precisely monitor and control the motional degrees of freedom of an object using light. These optomechanical interactions have inspired myriad proposals, ranging from quantum memories and transducers in quantum information networks to precision metrology of classical forces. Alongside advances in micro- and nano-fabrication, the burgeoning field of optomechanics has yielded a class of highly engineered systems designed to produce strong interactions between light and motion.

Optomechanical crystals are one such system in which the patterning of periodic holes in thin dielectric films traps both light and sound waves to a micro-scale volume. These devices feature strong radiation pressure coupling between high-quality optical cavity modes and internal nanomechanical resonances. Whether for applications in the quantum or classical domain, the utility of optomechanical crystals hinges on the degree to which light radiating from the device, having interacted with mechanical motion, can be collected and detected in an experimental apparatus consisting of conventional optical components such as lenses and optical fibers. While several efficient methods of optical coupling exist to meet this task, most are unsuitable for the cryogenic or vacuum integration required for many applications. The first portion of this dissertation will detail the development of robust and efficient methods of optically coupling optomechanical resonators to optical fibers, with an emphasis on fabrication processes and optical characterization.

I will then proceed to describe a few experiments enabled by the fiber couplers. The first studies the performance of an optomechanical resonator as a precise sensor for continuous position measurement. The sensitivity of the measurement, limited by the detection efficiency of intracavity photons, is compared to the standard quantum limit imposed by the quantum properties of the laser probe light. The added noise of the measurement is seen to fall within a factor of 3 of the standard quantum limit, representing an order of magnitude improvement over previous experiments utilizing optomechanical crystals, and matching the performance of similar measurements in the microwave domain.

The next experiment uses single photon counting to detect individual phonon emission and absorption events within the nanomechanical oscillator. The scattering of laser light from mechanical motion produces correlated photon-phonon pairs, and detection of the emitted photon corresponds to an effective phonon counting scheme. In the process of scattering, the coherence properties of the mechanical oscillation are mapped onto the reflected light. Intensity interferometry of the reflected light then allows measurement of the temporal coherence of the acoustic field. These correlations are measured for a range of experimental conditions, including the optomechanical amplification of the mechanics to a self-oscillation regime, and comparisons are drawn to a laser system for phonons. Finally, prospects for using phonon counting and intensity interferometry to produce non-classical mechanical states are detailed following recent proposals in literature.

Fractal dimension, wavelet shrinkage and anomaly detection for mine hunting

An anomaly detection approach is considered for the mine hunting in sonar imagery problem. The authors exploit previous work that used dual-tree wavelets and fractal dimension to adaptively suppress sand ripples and a matched filter as an initial detector. Here, lacunarity inspired features are extracted from the remaining false positives, again using dual-tree wavelets. A one-class support vector machine is then used to learn a decision boundary, based only on these false positives. The approach exploits the large quantities of 'normal' natural background data available but avoids the difficult requirement of collecting examples of targets in order to train a classifier. © 2012 The Institution of Engineering and Technology.