Three-dimensional localization of multiple acoustic sources in shallow ocean with non-Gaussian noise

In this paper, a low-complexity algorithm SAGE-USL is presented for 3-dimensional (3-D) localization of multiple acoustic sources in a shallow ocean with non-Gaussian ambient noise, using a vertical and a horizontal linear array of sensors. In the proposed method, noise is modeled as a Gaussian mixture. Initial estimates of the unknown parameters (source coordinates, signal waveforms and noise parameters) are obtained by known/conventional methods, and a generalized expectation maximization algorithm is used to update the initial estimates iteratively. Simulation results indicate that convergence is reached in a small number of (<= 10) iterations. Initialization requires one 2-D search and one 1-D search, and the iterative updates require a sequence of 1-D searches. Therefore the computational complexity of the SAGE-USL algorithm is lower than that of conventional techniques such as 3-D MUSIC by several orders of magnitude. We also derive the Cramer-Rao Bound (CRB) for 3-D localization of multiple sources in a range-independent ocean. Simulation results are presented to show that the root-mean-square localization errors of SAGE-USL are close to the corresponding CRBs and significantly lower than those of 3-D MUSIC. (C) 2014 Elsevier Inc. All rights reserved.

Generation of multiple sheets of light using spatial-filtering technique

We develop an optical system for generating multiple light sheets. This is enabled by employing a special class of spatial filters in a cylindrical lens geometry. The proposed binary filter placed at the back aperture of the cylindrical lens results in the generation of a periodic transverse pattern extending along the z axis (i.e., multiple light sheets). Experimental results confirm the generation of multiple light sheets of thickness 6.6 mu m with an intersheet spacing of 13.4 mu m. The proposed imaging technique may facilitate three-dimensional imaging in nano-optics, fluorescence microscopy, and nanobiology. (C) 2014 Optical Society of America

Optical properties of an inhomogeneously broadened Lambda V-system with multiple excited states

We present a theoretical model using a density matrix approach to show the influence of multiple excited states on the optical properties of an inhomogeneously broadened Lambda V-system of the Rb-87 D2 line. These closely spaced multiple excited states cause asymmetry in absorption and dispersion profiles. We observe the reduced absorption profiles, due to dressed state interactions of the applied electromagnetic fields, which results the Mollow sideband-like transparency windows. In a room temperature vapor, we obtain a narrow enhanced absorption and steep positive dispersion at the line center when the strengths of control and pump fields are equal. Here, we show how the probe transmittance varies when it passes through the atomic medium. We also discuss the transient behavior of our system which agrees well with the corresponding absorption and dispersion profiles. This study has potential applications in controllability of group velocity, and for optical and quantum information processing.

Implications of multiple scattering on the assessment of black carbon aerosol radiative forcing

The effects of radiative coupling between scattering and absorbing aerosols, in an external mixture, on the aerosol radiative forcing (ARF) due to black carbon (BC), its sensitivity to the composite aerosol loading and composition, and surface reflectance are investigated using radiative transfer model simulations. The ARF due to BC is found to depend significantly on the optical properties of the `neighboring' (non-BC) aerosol species. The scattering due to these species significantly increases the top of the atmospheric warming due to black carbon aerosols, and significant changes in the radiative forcing efficiency of BC. This is especially significant over dark surfaces (such as oceans), despite the ARF due to BC being higher over snow and land-surfaces. The spatial heterogeneity of this effect (coupling or multiple scattering by neighboring aerosol species) imposes large uncertainty in the estimation ARF due to BC aerosols, especially over the oceans. (C) 2014 Elsevier Ltd. All rights reserved.

Exclusive Detection of Sub-Nanomolar Levels of Palladium(II) in Water: An Excellent Probe for Multiple Applications

A new colorimetric probe has been developed for the detection and estimation of Pd-II at sub-nanomolar concentrations. The probe consisted of rhodamine (signaling unit), which was linked with a bis-picolyl moiety (binding site) through a phenyl ring. Pd-II induced opening of the spirolactam ring of the probe with the generation of a prominent pink color. The excellent selectivity of the probe towards Pd-II over Pd-0 or Rh-II ensured its potential utility for the detection of residual palladium contamination in pharma-ceutical drugs and in Pd-catalyzed reactions. The probe showed a ``turn-on'' (bright yellow) fluorescence upon the addition of Pd-II, which made it suitable for the detection of Pd contaminants in mammalian cells.

OFDM-Aided Differential Space-Time Shift Keying Using Iterative Soft Multiple-Symbol Differential Sphere Decoding

Soft-decision multiple-symbol differential sphere decoding (MSDSD) is proposed for orthogonal frequency-division multiplexing (OFDM)-aided differential space-time shift keying (DSTSK)-aided transmission over frequency-selective channels. Specifically, the DSTSK signaling blocks are generated by the channel-encoded source information and the space-time (ST) blocks are appropriately mapped to a number of OFDM subcarriers. After OFDM demodulation, the DSTSK signal is noncoherently detected by our soft-decision MSDSD detector. A novel soft-decision MSDSD detector is designed, and the associated decision rule is derived for the DSTSK scheme. Our simulation results demonstrate that an SNR reduction of 2 dB is achieved by the proposed scheme using an MSDSD window size of N-w = 4 over the conventional soft-decision-aided differential detection benchmarker, while communicating over dispersive channels and dispensing with channel estimation (CE).

Experimental Characterization and Control of Miniaturized Pneumatic Artificial Muscle

Robotic surgical tools used in minimally invasive surgeries (MIS) require miniaturized and reliable actuators for precise positioning and control of the end-effector. Miniature pneumatic artificial muscles (MPAMs) are a good choice due to their inert nature, high force to weight ratio, and fast actuation. In this paper, we present the development of miniaturized braided pneumatic muscles with an outer diameter of similar to 1.2 mm, a high contraction ratio of about 18%, and capable of providing a pull force in excess of 4 N at a supply pressure of 0.8 MPa. We present the details of the developed experimental setup, experimental data on contraction and force as a function of applied pressure, and characterization of the MPAM. We also present a simple kinematics and experimental data based model of the braided pneumatic muscle and show that the model predicts contraction in length to within 20% of the measured value. Finally, a robust controller for the MPAMs is developed and validated with experiments and it is shown that the MPAMs have a time constant of similar to 10 ms thereby making them suitable for actuating endoscopic and robotic surgical tools.

Fruit and Seed Volatiles: Multiple Stage Settings, Actors and Props in an Evolutionary Play

Plants emit volatile organic compounds (VOCs) from most parts of their anatomy. Conventionally, the volatiles of leaves, flowers, fruits and seeds have been investigated separately. This review presents an integrated perspective of volatiles produced by fruits and seeds in the context of selection on the whole plant. It suggests that fruit and seed volatiles may only be understood in the light of the chemistry of the whole plant. Fleshy fruit may be viewed as an ecological arena within which several evolutionary games are being played involving fruit VOCs. Fruit odour and colour may be correlated and interact via multimodal signalling in influencing visits by frugivores. The hypothesis of volatile crypsis in the evolution of hard seeds as protection against volatile diffusion and perception by seed predators is reviewed. Current views on the role of volatiles in ant dispersal of seeds or myrmecochory are summarised, especially the suggestion that ants are being manipulated by plants in the form of a sensory trap while providing this service. Plant VOC production is presented as an emergent phenotype that could result from multiple selection pressures acting on various plant parts; the ``plant'' phenotype and VOC profile may receive significant contributions from symbionts within the plant. Viewing the plant as a holobiont would benefit an understanding of the emergent plant phenotype.

Ionic Bonding between Artificial Atoms

Conventional solids are prepared from building blocks that are conceptually no larger than a hundred atoms. While van der Waals and dipole-dipole interactions also influence the formation of these materials, stronger interactions, referred to as chemical bonds, play a more decisive role in determining the structures of most solids. Chemical bonds that hold such materials together are said to be ionic, covalent, metallic, dative, or otherwise a combination of these. Solids that utilize semiconductor nanocrystal quantum dots as building units have been demonstrated to exist; however, the interparticle forces in such materials are decidedly not chemical. Here we demonstrate the formation of charge transfer states in a binary quantum dot mixture. Charge is observed to reside in quantum confined states of one of the participating quantum dots. These interactions lead to materials that may be regarded as the nanoscale analog of an ionic solid. The process by which these materials form has interesting parallels to chemical reactions in conventional chemistry.

A Kunitz-type serine protease inhibitor from Butea monosperma seed and its influence on developmental physiology of Helicoverpa armigera

A protease inhibitor from the seeds of Butea monosperma (BmPI) was purified, characterized and studied for its influence on developmental physiology of Helicover-pa armigera. BmPI on two-dimensional separations indicated the presence of a 14 kDa protein with an isoelectric point in the acidic region (pl 5.6). Multiple Sequence Analysis data suggested that the BmPI contains a sequence motif which is conserved in various trypsin and chymotrypsin inhibitors of Kunitz-type. The inhibitor exhibited trypsin inhibitory activity in a broad range of pH (4-10) and temperature (10-80 degrees C). The enzyme kinetic studies revealed BmPI as a competitive inhibitor with a K-i value of 1.2 x 10(-9) M. In vitro studies with BmPI indicated measurable inhibitory activity on total gut proteolytic enzymes of H. armigera (IC(50)2.0 mu g/ml) and bovine trypsin. BmPI supplemented artificial diet caused dose dependent mortality and reduction in growth and weight. The fertility and fecundity of H. armigera, declined whereas the larval-pupal duration of the insect life cycle extended. These detrimental effects on H. armigera suggest the usefulness of BmPl in insect pest management of food crops. (C) 2014 Elsevier Ltd. All rights reserved.

GLOBAL REGISTRATION OF MULTIPLE POINT CLOUDS USING SEMIDEFINITE PROGRAMMING

Consider N points in R-d and M local coordinate systems that are related through unknown rigid transforms. For each point, we are given (possibly noisy) measurements of its local coordinates in some of the coordinate systems. Alternatively, for each coordinate system, we observe the coordinates of a subset of the points. The problem of estimating the global coordinates of the N points (up to a rigid transform) from such measurements comes up in distributed approaches to molecular conformation and sensor network localization, and also in computer vision and graphics. The least-squares formulation of this problem, although nonconvex, has a well-known closed-form solution when M = 2 (based on the singular value decomposition (SVD)). However, no closed-form solution is known for M >= 3. In this paper, we demonstrate how the least-squares formulation can be relaxed into a convex program, namely, a semidefinite program (SDP). By setting up connections between the uniqueness of this SDP and results from rigidity theory, we prove conditions for exact and stable recovery for the SDP relaxation. In particular, we prove that the SDP relaxation can guarantee recovery under more adversarial conditions compared to earlier proposed spectral relaxations, and we derive error bounds for the registration error incurred by the SDP relaxation. We also present results of numerical experiments on simulated data to confirm the theoretical findings. We empirically demonstrate that (a) unlike the spectral relaxation, the relaxation gap is mostly zero for the SDP (i.e., we are able to solve the original nonconvex least-squares problem) up to a certain noise threshold, and (b) the SDP performs significantly better than spectral and manifold-optimization methods, particularly at large noise levels.

Use of Data Driven Techniques for Short Lead Time Streamflow Forecasting in Mahanadi basin

Streamflow forecasts at daily time scale are necessary for effective management of water resources systems. Typical applications include flood control, water quality management, water supply to multiple stakeholders, hydropower and irrigation systems. Conventionally physically based conceptual models and data-driven models are used for forecasting streamflows. Conceptual models require detailed understanding of physical processes governing the system being modeled. Major constraints in developing effective conceptual models are sparse hydrometric gauge network and short historical records that limit our understanding of physical processes. On the other hand, data-driven models rely solely on previous hydrological and meteorological data without directly taking into account the underlying physical processes. Among various data driven models Auto Regressive Integrated Moving Average (ARIMA), Artificial Neural Networks (ANNs) are most widely used techniques. The present study assesses performance of ARIMA and ANNs methods in arriving at one-to seven-day ahead forecast of daily streamflows at Basantpur streamgauge site that is situated at upstream of Hirakud Dam in Mahanadi river basin, India. The ANNs considered include Feed-Forward back propagation Neural Network (FFNN) and Radial Basis Neural Network (RBNN). Daily streamflow forecasts at Basantpur site find use in management of water from Hirakud reservoir. (C) 2015 The Authors. Published by Elsevier B.V.

Energy Sharing for Multiple Sensor Nodes With Finite Buffers

We consider the problem of finding optimal energy sharing policies that maximize the network performance of a system comprising of multiple sensor nodes and a single energy harvesting (EH) source. Sensor nodes periodically sense the random field and generate data, which is stored in the corresponding data queues. The EH source harnesses energy from ambient energy sources and the generated energy is stored in an energy buffer. Sensor nodes receive energy for data transmission from the EH source. The EH source has to efficiently share the stored energy among the nodes to minimize the long-run average delay in data transmission. We formulate the problem of energy sharing between the nodes in the framework of average cost infinite-horizon Markov decision processes (MDPs). We develop efficient energy sharing algorithms, namely Q-learning algorithm with exploration mechanisms based on the epsilon-greedy method as well as upper confidence bound (UCB). We extend these algorithms by incorporating state and action space aggregation to tackle state-action space explosion in the MDP. We also develop a cross entropy based method that incorporates policy parameterization to find near optimal energy sharing policies. Through simulations, we show that our algorithms yield energy sharing policies that outperform the heuristic greedy method.

Robust design of multiple trailing edge flaps for helicopter vibration reduction: A multi-objective bat algorithm approach

The objective of this study is to determine an optimal trailing edge flap configuration and flap location to achieve minimum hub vibration levels and flap actuation power simultaneously. An aeroelastic analysis of a soft in-plane four-bladed rotor is performed in conjunction with optimal control. A second-order polynomial response surface based on an orthogonal array (OA) with 3-level design describes both the objectives adequately. Two new orthogonal arrays called MGB2P-OA and MGB4P-OA are proposed to generate nonlinear response surfaces with all interaction terms for two and four parameters, respectively. A multi-objective bat algorithm (MOBA) approach is used to obtain the optimal design point for the mutually conflicting objectives. MOBA is a recently developed nature-inspired metaheuristic optimization algorithm that is based on the echolocation behaviour of bats. It is found that MOBA inspired Pareto optimal trailing edge flap design reduces vibration levels by 73% and flap actuation power by 27% in comparison with the baseline design.