Examining the Effectiveness of Discriminant Function Analysis and Cluster Analysis in Species Identification of Male Field Crickets Based on Their Calling Songs

Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification.

A two-axis in-plane motion measurement system based on optical beam deflection

Measurement of in-plane motion with high resolution and large bandwidth enables model-identification and real-time control of motion-stages. This paper presents an optical beam deflection based system for measurement of in-plane motion of both macro- and micro-scale motion stages. A curved reflector is integrated with the motion stage to achieve sensitivity to in-plane translational motion along two axes. Under optimal settings, the measurement system is shown to theoretically achieve sub-angstrom measurement resolution over a bandwidth in excess of 1 kHz and negligible cross-sensitivity to linear motion. Subsequently, the proposed technique is experimentally demonstrated by measuring the in-plane motion of a piezo flexure stage and a scanning probe microcantilever. For the former case, reflective spherical balls of different radii are employed to measure the in-plane motion and the measured sensitivities are shown to agree with theoretical values, on average, to within 8.3%. For the latter case, a prototype polydimethylsiloxane micro-reflector is integrated with the microcantilever. The measured in-plane motion of the microcantilever probe is used to identify nonlinearities and the transient dynamics of the piezo-stage upon which the probe is mounted. These are subsequently compensated by means of feedback control. (C) 2013 AIP Publishing LLC.

Antenna selection for time-varying channels based on slepian subspace projections

Single receive antenna selection (AS) allows single-input single-output (SISO) systems to retain the diversity benefits of multiple antennas with minimum hardware costs. We propose a single receive AS method for time-varying channels, in which practical limitations imposed by next-generation wireless standards such as training, packetization and antenna switching time are taken into account. The proposed method utilizes low-complexity subspace projection techniques spanned by discrete prolate spheroidal (DPS) sequences. It only uses Doppler bandwidth knowledge, and does not need detailed correlation knowledge. Results show that the proposed AS method outperforms ideal conventional SISO systems with perfect CSI but no AS at the receiver and AS using the conventional Fourier estimation/prediction method. A closed-form expression for the symbol error probability (SEP) of phase-shift keying (MPSK) with symbol-by-symbol receive AS is derived.

Epoch extraction based on integrated linear prediction residual using plosion index

Epoch is defined as the instant of significant excitation within a pitch period of voiced speech. Epoch extraction continues to attract the interest of researchers because of its significance in speech analysis. Existing high performance epoch extraction algorithms require either dynamic programming techniques or a priori information of the average pitch period. An algorithm without such requirements is proposed based on integrated linear prediction residual (ILPR) which resembles the voice source signal. Half wave rectified and negated ILPR (or Hilbert transform of ILPR) is used as the pre-processed signal. A new non-linear temporal measure named the plosion index (PI) has been proposed for detecting `transients' in speech signal. An extension of PI, called the dynamic plosion index (DPI) is applied on pre-processed signal to estimate the epochs. The proposed DPI algorithm is validated using six large databases which provide simultaneous EGG recordings. Creaky and singing voice samples are also analyzed. The algorithm has been tested for its robustness in the presence of additive white and babble noise and on simulated telephone quality speech. The performance of the DPI algorithm is found to be comparable or better than five state-of-the-art techniques for the experiments considered.

Supercapacitors based on nitrogen-doped reduced graphene oxide and borocarbonitrides

Nitrogen-doped reduced giaphene oxide (RGO) samples with different nitrogen content, prepared by two different methods, as well as nitrogen-doped few-layer graphene have been investigated as supercapacitor electrodes. Two electrode measurements have been carried out both in aqueous (6 M KOH) and in ionic liquid media. Nitrogen-doped reduced graphene oxides exhibit satisfactory specific capacitance, the values reaching 126 F/g at a scan rate of 10 mV/s in aqueous medium. Besides providing supercapacitor characteristics, the study has shown the nitrogen content and surface area to be important factors. High surface-area borocarbonitrides, BxCyNz, prepared by the urea route appear to be excellent supercapacitor electrode materials. Thus, BC4.5N exhibits a specific capacitance of 169 F/g at a scan rate of 10 mV/s in aqueous medium. In an ionic liquid medium, nitrogen-doped RGO and BC4.5N exhibit specific capacitance values of 258 F/g and 240 F/g at a scan rate of 5 mV/s. The ionic liquid enables a larger operating voltage range of 0.0-2.5 V compared to 0.0-1 V in aqueous medium. (C) 2013 Elsevier Ltd. All rights reserved.

mulPBA: an efficient multiple protein structure alignment method based on a structural alphabet

The increasing number of available protein structures requires efficient tools for multiple structure comparison. Indeed, multiple structural alignments are essential for the analysis of function, evolution and architecture of protein structures. For this purpose, we proposed a new web server called multiple Protein Block Alignment (mulPBA). This server implements a method based on a structural alphabet to describe the backbone conformation of a protein chain in terms of dihedral angles. This sequence-like' representation enables the use of powerful sequence alignment methods for primary structure comparison, followed by an iterative refinement of the structural superposition. This approach yields alignments superior to most of the rigid-body alignment methods and highly comparable with the flexible structure comparison approaches. We implement this method in a web server designed to do multiple structure superimpositions from a set of structures given by the user. Outputs are given as both sequence alignment and superposed 3D structures visualized directly by static images generated by PyMol or through a Jmol applet allowing dynamic interaction. Multiple global quality measures are given. Relatedness between structures is indicated by a distance dendogram. Superimposed structures in PDB format can be also downloaded, and the results are quickly obtained. mulPBA server can be accessed at www.dsimb.inserm.fr/dsimb_tools/mulpba/.

Optimum steering input determination and path-tracking of all-wheel steer vehicles on uneven terrains based on constrained optimization

In this paper we propose a framework for optimum steering input determination of all-wheel steer vehicles (AWSV) on rough terrains. The framework computes the steering input which minimizes the tracking error for a given trajectory. Unlike previous methodologies of computing steering inputs of car-like vehicles, the proposed methodology depends explicitly on the vehicle dynamics and can be extended to vehicle having arbitrary number of steering inputs. A fully generic framework has been used to derive the vehicle dynamics and a non-linear programming based constrained optimization approach has been used to compute the steering input considering the instantaneous vehicle dynamics, no-slip and contact constraints of the vehicle. All Wheel steer Vehicles have a special parallel steering ability where the instantaneous centre of rotation (ICR) is at infinity. The proposed framework automatically enables the vehicle to choose between parallel steer and normal operation depending on the error with respect to the desired trajectory. The efficacy of the proposed framework is proved by extensive uneven terrain simulations, for trajectories with continuous or discontinuous velocity profile.

Multivariate Granger causality: an estimation framework based on factorization of the spectral density matrix

Granger causality is increasingly being applied to multi-electrode neurophysiological and functional imaging data to characterize directional interactions between neurons and brain regions. For a multivariate dataset, one might be interested in different subsets of the recorded neurons or brain regions. According to the current estimation framework, for each subset, one conducts a separate autoregressive model fitting process, introducing the potential for unwanted variability and uncertainty. In this paper, we propose a multivariate framework for estimating Granger causality. It is based on spectral density matrix factorization and offers the advantage that the estimation of such a matrix needs to be done only once for the entire multivariate dataset. For any subset of recorded data, Granger causality can be calculated through factorizing the appropriate submatrix of the overall spectral density matrix.

Large-MIMO Receiver based on Linear Regression of MMSE Residual

Multiple input multiple output (MIMO) systems with large number of antennas have been gaining wide attention as they enable very high throughputs. A major impediment is the complexity at the receiver needed to detect the transmitted data. To this end we propose a new receiver, called LRR (Linear Regression of MMSE Residual), which improves the MMSE receiver by learning a linear regression model for the error of the MMSE receiver. The LRR receiver uses pilot data to estimate the channel, and then uses locally generated training data (not transmitted over the channel), to find the linear regression parameters. The proposed receiver is suitable for applications where the channel remains constant for a long period (slow-fading channels) and performs quite well: at a bit error rate (BER) of 10(-3), the SNR gain over MMSE receiver is about 7 dB for a 16 x 16 system; for a 64 x 64 system the gain is about 8.5 dB. For large coherence time, the complexity order of the LRR receiver is the same as that of the MMSE receiver, and in simulations we find that it needs about 4 times as many floating point operations. We also show that further gain of about 4 dB is obtained by local search around the estimate given by the LRR receiver.

A New Voltage Stability Index based on the Tangent Vector of the Power Flow Jacobian

This paper presents a new voltage stability index based on the tangent vector of the power flow jacobian. This index is capable of providing the relative vulnerability information of the system buses from the point of view of voltage collapse. In an effort to compare this index with a similar index, the popular voltage stability index L is studied and it is shown through system studies that the L index is not a very consistent indicator of the voltage collapse point of the system but is only a reasonable indicator of the vulnerability of the system buses to voltage collapse. We also show that the new index can be used in the voltage stability analysis of radial systems which is not possible with the L index. This is a significant result of this investigation since there is a lot of contemporary interest in distributed generation and microgrids which are by and large radial in nature. Simulation results considering several test systems are provided to validate the results and the computational needs of the proposed scheme is assessed in comparison with other schemes

Tripodal Bile Acid Architectures Based on a Triarylphosphine Oxide Core Obtained by Copper-Catalysed 1,3]-Dipolar Cycloaddition: Synthesis and Preliminary Aggregation Studies

We report the synthesis and aggregation behaviour of new water-soluble, bile acid derived tripodal architectures based on a core derived from triphenylphosphine oxide. We employed the well-established copper-catalysed 1,3]-dipolar cycloaddition (CuAAC) for the construction of these tripodal molecules. The aggregation behaviour of these molecules in aqueous media was studied by different analytical methods such as dye solubilisation, dynamic light scattering, NMR and AFM. These molecular architectures also offer an additional advantage in aiding understanding of the influence of the nature of the bile acid backbone and of the configuration at the steroid C-3 position in these architectures; to the best of our knowledge this has not been reported in the literature. The unique gelation properties of the -derivatives were explained through molecular modelling studies and the mechanical behaviour of these gels was studied by rheology experiments.

Optical bio-sensing devices based on etched fiber Bragg gratings coated with carbon nanotubes and graphene oxide along with a specific dendrimer

We demonstrate that etched fiber Bragg gratings (eFBGs) coated with single walled carbon nanotubes (SWNTs) and graphene oxide (GO) are highly sensitive and accurate biochemical sensors. Here, for detecting protein concanavalin A (Con A), mannose-functionalized poly(propyl ether imine) (PETIM) dendrimers (DMs) have been attached to the SWNTs (or GO) coated on the surface modified eFBG. The dendrimers act as multivalent ligands, having specificity to detect lectin Con A. The specificity of the sensor is shown by a much weaker response (factor of similar to 2500 for the SWNT and similar to 2000 for the GO coated eFBG) to detect non specific lectin peanut agglutinin. DM molecules functionalized GO coated eFBG sensors showed excellent specificity to Con A even in the presence of excess amount of an interfering protein bovine serum albumin. The shift in the Bragg wavelength (Delta lambda(B)) with respect to the lambda(B) values of SWNT (or GO)-DM coated eFBG for various concentrations of lectin follows Langmuir type adsorption isotherm, giving an affinity constant of similar to 4 x 10(7) M-1 for SWNTs coated eFBG and similar to 3 x 10(8) M-1 for the GO coated eFBG. (C) 2014 Elsevier B.V. All rights reserved.

Glacial mass balance changes in the Karakoram and Himalaya based on CMIP5 multi-model climate projections

The impact of future climate change on the glaciers in the Karakoram and Himalaya (KH) is investigated using CMIP5 multi-model temperature and precipitation projections, and a relationship between glacial accumulation-area ratio and mass balance developed for the region based on the last 30 to 40 years of observational data. We estimate that the current glacial mass balance (year 2000) for the entire KH region is -6.6 +/- 1 Gta(-1), which decreases about sixfold to -35 +/- 2 Gta(-1) by the 2080s under the high emission scenario of RCP8.5. However, under the low emission scenario of RCP2.6 the glacial mass loss only doubles to -12 +/- 2 Gta(-1) by the 2080s. We also find that 10.6 and 27 % of the glaciers could face `eventual disappearance' by the end of the century under RCP2.6 and RCP8.5 respectively, underscoring the threat to water resources under high emission scenarios.

Accurate point matching based on multi-objective Genetic Algorithm for multi-sensor satellite imagery

This paper investigates a novel approach for point matching of multi-sensor satellite imagery. The feature (corner) points extracted using an improved version of the Harris Corner Detector (HCD) is matched using multi-objective optimization based on a Genetic Algorithm (GA). An objective switching approach to optimization that incorporates an angle criterion, distance condition and point matching condition in the multi-objective fitness function is applied to match corresponding corner-points between the reference image and the sensed image. The matched points obtained in this way are used to align the sensed image with a reference image by applying an affine transformation. From the results obtained, the performance of the image registration is evaluated and compared with existing methods, namely Nearest Neighbor-Random SAmple Consensus (NN-Ran-SAC) and multi-objective Discrete Particle Swarm Optimization (DPSO). From the performed experiments it can be concluded that the proposed approach is an accurate method for registration of multi-sensor satellite imagery. (C) 2014 Elsevier Inc. All rights reserved.