Toward resolving deep neoaves phylogeny : data, signal enhancement, and priors

We report three developments toward resolving the challenge of the apparent basal polytomy of neoavian birds. First, we describe improved conditional down-weighting techniques to reduce noise relative to signal for deeper divergences and find increased agreement between data sets. Second, we present formulae for calculating the probabilities of finding predefined groupings in the optimal tree. Finally, we report a significant increase in data: nine new mitochondrial (mt) genomes (the dollarbird, New Zealand kingfisher, great potoo, Australian owlet-nightjar, white-tailed trogon, barn owl, a roadrunner [a ground cuckoo], New Zealand long-tailed cuckoo, and the peach-faced lovebird) and together they provide data for each of the six main groups of Neoaves proposed by Cracraft J (2001). We use his six main groups of modern birds as priors for evaluation of results. These include passerines, cuckoos, parrots, and three other groups termed “WoodKing” (woodpeckers/rollers/kingfishers), “SCA” (owls/potoos/owlet-nightjars/hummingbirds/swifts), and “Conglomerati.” In general, the support is highly significant with just two exceptions, the owls move from the “SCA” group to the raptors, particularly accipitrids (buzzards/eagles) and the osprey, and the shorebirds may be an independent group from the rest of the “Conglomerati”. Molecular dating mt genomes support a major diversification of at least 12 neoavian lineages in the Late Cretaceous. Our results form a basis for further testing with both nuclear-coding sequences and rare genomic changes.

Are plasmons responsible for the Raman signal enhancement observed with gold nanoparticle sensors?

The electromagnetic enhancement that occurs in surface enhanced Raman scattering (SERS) substrates containing gold nanoparticles (NPs) is believed to arise through the generation of localised surface plasmons. We present results that show no SERS signals are obtained when 25 nm diameter gold NPs layered quartz substrates exposed to 2-aminopyridine are illuminated with plasmon resonant 532 nm radiation, but SERS signals are observed when the same samples are illuminated with non-resonant 785 nm radiation.

Enhancing Raman signal sufficiently for practical sensing applications

Techniques are presented for enhancing weak Raman scattering signals for rapid yet accurate substance detection. Novel surfaces that allow signal enhancement quantification are described as are eye-safe methodologies that maximize the stand-off Raman detection range.

Clustered blind beamforming from ad-hoc microphone arrays

Microphone arrays have been used in various applications to capture conversations, such as in meetings and teleconferences. In many cases, the microphone and likely source locations are known \emph{a priori}, and calculating beamforming filters is therefore straightforward. In ad-hoc situations, however, when the microphones have not been systematically positioned, this information is not available and beamforming must be achieved blindly. In achieving this, a commonly neglected issue is whether it is optimal to use all of the available microphones, or only an advantageous subset of these. This paper commences by reviewing different approaches to blind beamforming, characterising them by the way they estimate the signal propagation vector and the spatial coherence of noise in the absence of prior knowledge of microphone and speaker locations. Following this, a novel clustered approach to blind beamforming is motivated and developed. Without using any prior geometrical information, microphones are first grouped into localised clusters, which are then ranked according to their relative distance from a speaker. Beamforming is then performed using either the closest microphone cluster, or a weighted combination of clusters. The clustered algorithms are compared to the full set of microphones in experiments on a database recorded on different ad-hoc array geometries. These experiments evaluate the methods in terms of signal enhancement as well as performance on a large vocabulary speech recognition task.

Effectiveness of MED for Fault Diagnosis in Roller Bearings

Diagnostics of rolling element bearings is usually performed by means of vibration signals measured by accelerometers placed in the proximity of the bearing under investigation. The aim is to monitor the integrity of the bearing components, in order to avoid catastrophic failures, or to implement condition based maintenance strategies. In particular, the trend in this field is to combine in a single algorithm different signal-enhancement and signal-analysis techniques. Among the first ones, Minimum Entropy Deconvolution (MED) has been pointed out as a key tool able to highlight the effect of a possible damage in one of the bearing components within the vibration signal. This paper presents the application of this technique to signals collected on a simple test-rig, able to test damaged industrial roller bearings in different working conditions. The effectiveness of the technique has been tested, comparing the results of one undamaged bearing with three bearings artificially damaged in different locations, namely on the inner race, outer race and rollers. Since MED performances are dependent on the filter length, the most suitable value of this parameter is defined on the basis of both the application and measured signals. This represents an original contribution of the paper.

Ultra sensitive label free surface enhanced Raman spectroscopy method for the detection of biomolecules

We present a proof of concept for a novel nanosensor for the detection of ultra-trace amounts of bio-active molecules in complex matrices. The nanosensor is comprised of gold nanoparticles with an ultra-thin silica shell and antibody surface attachment, which allows for the immobilization and direct detection of bio-active molecules by surface enhanced Raman spectroscopy (SERS) without requiring a Raman label. The ultra-thin passive layer (~1.3 nm thickness) prevents competing molecules from binding non-selectively to the gold surface without compromising the signal enhancement. The antibodies attached on the surface of the nanoparticles selectively bind to the target molecule with high affinity. The interaction between the nanosensor and the target analyte result in conformational rearrangements of the antibody binding sites, leading to significant changes in the surface enhanced Raman spectra of the nanoparticles when compared to the spectra of the un-reacted nanoparticles. Nanosensors of this design targeting the bio-active compounds erythropoietin and caffeine were able to detect ultra-trace amounts the analyte to the lower quantification limits of 3.5×10−13 M and 1×10−9 M, respectively.

Hybrid polymer/metal nanoparticles with surface enhanced raman tracking for potential use in nanomedicine

This project was a preliminary step towards the development of novel methods for early stage cancer diagnosis and treatment. Diagnostic imaging agents with high Raman signal enhancement were developed based on tailored assemblies of gold nanoparticles, which demonstrated potential for non-invasive detection from deep under the skin surface. Specifically designed polymers were employed to assemble gold nanoparticles into controlled morphologies including dimers, nanochains, nanoplates, globular and core-satellite nanostructures. Our findings suggest that the Raman enhancement is strongly dependent on assembly morphology and can be tuned to adapt to the requirements of the diagnostic agent.

An acoustically enhanced gold film Raman sensor on a lithium niobate substrate

The surface enhanced Raman scattering effect has shown immense potential for detecting trace amounts of explosive vapor molecules. To date, efforts to produce a commercially available, reliable SERS sensor have been impeded by an inability to separate the electromagnetic enhancement produced by the metallic nanostructure from other signal enhancing effects. Here, we show a new Raman sensor that uses surface acoustic waves (SAWs) to produce controllable surface structures on gold films deposited on LiNbO3 substrates that modulate the Raman signal of a target compound (thiophenol) adsorbed on the films. We demonstrate that this sensor can dynamically control the Raman signal simply by changing the SAW’s amplitude, allowing the Raman signal enhancement factor to be directly measured with no variation in the concentration of the target compound. The physically adsorbed molecules can be removed from the sensor without physical cleaning or damage, making it possible to reuse it for real-time Raman detection.

Plasmon-tuned silver colloids for SERRS analysis of methemoglobin with preserved nativity

Optically tuned silver nanoparticles (AgNP's) functionalized with ω-mercaptoalkanoic acids are synthesized and used as a signal amplifier for the surface-enhanced resonance Raman scattering (SERRS) study of heme cofactor in methemoglobin (metHb). Even though both mercaptopropionic acid (MPA)- and mercaptononanoic acid (MNA)-functionalized AgNP's exemplify vastly enhanced SERRS signal of metHb, MNA-AgNP's amplify the SERRS signal amid preservation of the nativity of the heme pocket, unlike MPA-AgNP's. The electrostatic interaction between MNA-AgNP's and metHb leads to instant signal enhancement with a Raman enhancement factor (EF(SERS)) of 4.2 × 10(3). Additionally, a Langmuir adsorption isotherm has been employed for the adsorption of metHb on the MNA-AgNP surface, which provides the real surface coverage and equilibrium constant (K) of metHb as 139 nM and 3.6 × 10(8) M(-1), respectively. The lowest detection limit of 10 nM for metHb has been demonstrated using MNA-AgNP's besides retaining the nativity of the heme pocket.

Functionalized Ag nanoparticles with tunable optical properties for selective protein analysis

We present a preparation procedure for small sized biocompatibly coated Ag nanoparticles with tunable surface plasmon resonances. The conditions were optimised with respect to the resonance Raman signal enhancement of heme proteins and to the preservation of the native protein structure....

Reproducible and label-free biosensor for the selective extraction and rapid detection of proteins in biological fluids

Erythropoietin (EPO), a glycoprotein hormone of ∼34 kDa, is an important hematopoietic growth factor, mainly produced in the kidney and controls the number of red blood cells circulating in the blood stream. Sensitive and rapid recombinant human EPO (rHuEPO) detection tools that improve on the current laborious EPO detection techniques are in high demand for both clinical and sports industry. A sensitive aptamer-functionalized biosensor (aptasensor) has been developed by controlled growth of gold nanostructures (AuNS) over a gold substrate (pAu/AuNS). The aptasensor selectively binds to rHuEPO and, therefore, was used to extract and detect the drug from horse plasma by surface enhanced Raman spectroscopy (SERS). Due to the nanogap separation between the nanostructures, the high population and distribution of hot spots on the pAu/AuNS substrate surface, strong signal enhancement was acquired. By using wide area illumination (WAI) setting for the Raman detection, a low RSD of 4.92% over 150 SERS measurements was achieved. The significant reproducibility of the new biosensor addresses the serious problem of SERS signal inconsistency that hampers the use of the technique in the field. The WAI setting is compatible with handheld Raman devices. Therefore, the new aptasensor can be used for the selective extraction of rHuEPO from biological fluids and subsequently screened with handheld Raman spectrometer for SERS based in-field protein detection.

Utility of USPIO-enhanced MR imaging to identify inflammation and the fibrous cap: A comparison of symptomatic and asymptomatic individuals

Background and purpose: Inflammation is a risk factor the vulnerable atheromatous plaque. This can be detected in vivo on high-resolution magnetic resonance (MR) imaging using a contrast agent, Sinerem™, an ultra-small super-paramagnetic iron oxide (USPIO). The aim of this study was to explore whether there is a difference in the degree of MR defined inflammation using USPIO particles, between symptomatic and asymptomatic carotid plaques. We report further on its T1 effect of enhancing the fibrous cap, which may allow dual contrast resolution of carotid atheroma. Methods: Twenty patients with carotid stenosis (10 symptomatic and 10 asymptomatic) underwent multi-sequence MR imaging before and 36 h post-USPIO infusion. Images were manually segmented into quadrants and signal change in each quadrant was calculated following USPIO administration. Mean signal change across all quadrants were compared between the two groups. Results: Symptomatic patients had significantly more quadrants with a signal drop than asymptomatic individuals (75% vs. 32%, p < 0.01). Asymptomatic plaques had more quadrants with signal enhancement than symptomatic ones (68% vs. 25%, p < 0.05); their mean signal change was also higher (46% vs. 15%, p < 0.01) and this appeared to correlate with a thicker fibrous cap on histology. Conclusions: Symptomatic patients had more quadrants with signal drop suggesting larger inflammatory infiltrates. Asymptomatic individuals showed significantly more enhancement possibly suggesting greater stability as a result of thicker fibrous caps. However, some asymptomatic plaques also had focal areas of signal drop, suggesting an occult macrophage burden. If validated by larger studies, USPIO may be a useful dual contrast agent able to improve risk stratification of patients with carotid stenosis and inform selection for intervention.

FPGA implementation of dual-microphone delay-and-sum beamforming for in-car speech enhancement and recognition

In an automotive environment, the performance of a speech recognition system is affected by environmental noise if the speech signal is acquired directly from a microphone. Speech enhancement techniques are therefore necessary to improve the speech recognition performance. In this paper, a field-programmable gate array (FPGA) implementation of dual-microphone delay-and-sum beamforming (DASB) for speech enhancement is presented. As the first step towards a cost-effective solution, the implementation described in this paper uses a relatively high-end FPGA device to facilitate the verification of various design strategies and parameters. Experimental results show that the proposed design can produce output waveforms close to those generated by a theoretical (floating-point) model with modest usage of FPGA resources. Speech recognition experiments are also conducted on enhanced in-car speech waveforms produced by the FPGA in order to compare recognition performance with the floating-point representation running on a PC.