Development of a global inundation map at high spatial resolution from topographic downscaling of coarse-scale remote sensing data

Large-scale estimates of the area of terrestrial surface waters have greatly improved over time, in particular through the development of multi-satellite methodologies, but the generally coarse spatial resolution (tens of kms) of global observations is still inadequate for many ecological applications. The goal of this study is to introduce a new, globally applicable downscaling method and to demonstrate its applicability to derive fine resolution results from coarse global inundation estimates. The downscaling procedure predicts the location of surface water cover with an inundation probability map that was generated by bagged derision trees using globally available topographic and hydrographic information from the SRTM-derived HydroSHEDS database and trained on the wetland extent of the GLC2000 global land cover map. We applied the downscaling technique to the Global Inundation Extent from Multi-Satellites (GIEMS) dataset to produce a new high-resolution inundation map at a pixel size of 15 arc-seconds, termed GIEMS-D15. GIEMS-D15 represents three states of land surface inundation extents: mean annual minimum (total area, 6.5 x 10(6) km(2)), mean annual maximum (12.1 x 10(6) km(2)), and long-term maximum (173 x 10(6) km(2)); the latter depicts the largest surface water area of any global map to date. While the accuracy of GIEMS-D15 reflects distribution errors introduced by the downscaling process as well as errors from the original satellite estimates, overall accuracy is good yet spatially variable. A comparison against regional wetland cover maps generated by independent observations shows that the results adequately represent large floodplains and wetlands. GIEMS-D15 offers a higher resolution delineation of inundated areas than previously available for the assessment of global freshwater resources and the study of large floodplain and wetland ecosystems. The technique of applying inundation probabilities also allows for coupling with coarse-scale hydro-climatological model simulations. (C) 2014 Elsevier Inc All rights reserved.

Quorum Sensing and Biofilm Formation in Mycobacteria: Role of c-di-GMP and Methods to Study This Second Messenger

Bacteria have evolved to survive the ever-changing environment using intriguing mechanisms of quorum sensing (QS). Very often, QS facilitates formation of biofilm to help bacteria to persist longer and the formation of such biofilms is regulated by c-di-GMP. It is a well-known second messenger also found in mycobacteria. Several methods have been developed to study c-di-GMP signaling pathways in a variety of bacteria. In this review, we have attempted to highlight a connection between c-di-GMP and biofilm formation and QS in mycobacteria and several methods that have helped in better understanding of c-di-GMP signaling. (c) 2014 IUBMB Life, 66(12):823-834, 2014

Faster computation of the Karhunen-Loeve expansion using its domain independence property

The goal of this work is to reduce the cost of computing the coefficients in the Karhunen-Loeve (KL) expansion. The KL expansion serves as a useful and efficient tool for discretizing second-order stochastic processes with known covariance function. Its applications in engineering mechanics include discretizing random field models for elastic moduli, fluid properties, and structural response. The main computational cost of finding the coefficients of this expansion arises from numerically solving an integral eigenvalue problem with the covariance function as the integration kernel. Mathematically this is a homogeneous Fredholm equation of second type. One widely used method for solving this integral eigenvalue problem is to use finite element (FE) bases for discretizing the eigenfunctions, followed by a Galerkin projection. This method is computationally expensive. In the current work it is first shown that the shape of the physical domain in a random field does not affect the realizations of the field estimated using KL expansion, although the individual KL terms are affected. Based on this domain independence property, a numerical integration based scheme accompanied by a modification of the domain, is proposed. In addition to presenting mathematical arguments to establish the domain independence, numerical studies are also conducted to demonstrate and test the proposed method. Numerically it is demonstrated that compared to the Galerkin method the computational speed gain in the proposed method is of three to four orders of magnitude for a two dimensional example, and of one to two orders of magnitude for a three dimensional example, while retaining the same level of accuracy. It is also shown that for separable covariance kernels a further cost reduction of three to four orders of magnitude can be achieved. Both normal and lognormal fields are considered in the numerical studies. (c) 2014 Elsevier B.V. All rights reserved.

Graphene on Paper: A Simple, Low-Cost Chemical Sensing Platform

Graphene layers have been transferred directly on to paper without any intermediate layers to yield G-paper. Resistive gas sensors have been fabricated using strips of G-paper. These sensors achieved a remarkable lower limit of detection of similar to 300 parts per trillion (ppt) for NO2, which is comparable to or better than those from other paper-based sensors. Ultraviolet exposure was found to dramatically reduce the recovery time and improve response times. G-paper sensors are also found to be robust against minor strain, which was also found to increase sensitivity. G-paper is expected to enable a simple and inexpensive low-cost flexible graphene platform

Synthesis and electrocatalytic properties of manganese dioxide for non-enzymatic hydrogen peroxide sensing

Manganese dioxide nanoparticles were synthesized by chemical reduction route at different growth temperatures of 40 degrees C, 80 degrees C, 100 degrees C and were characterized using X-ray Diffraction (XRD), Field emission scanning electron microscopy (FESEM), X-ray photoelectron spectroscopy (XPS), Cyclic Voltammetry (CV) and chronoamperometry (CA) analysis. FESEM results show that on increasing growth temperature the morphology changes from clusters into mixture of rods and flakes. XPS analysis reveals the formation of MnO2. Then these particles were immobilized on Pt electrode. A platinum (Pt) electrode modified with low dimensional MnO2 was investigated as a chronoamperometric (CA) sensor for hydrogen peroxide sensing (H2O2). The sample prepared at 100 degrees C shows good electrocatalytic ability for H2O2 sensing when compared with the samples prepared at 40 degrees C and 80 degrees C. At an operating potential of 0.3 V vs. Ag/AgCl catalytic oxidation of the analyte is measured for chronoamperometric (CA) monitoring. The CA signals are linearly proportional to the concentration of H2O2. It is also found that the morphology of the nanostructure plays a vital role in the detection of H2O2. (C) 2014 Elsevier Ltd. All rights reserved.

Effect of Pt doping on the gas sensing properties of porous chromium oxide films through a kinetic response analysis approach

The effect of doping trace amounts of noblemetals (Pt) on the gas sensing properties of chromium oxide thin films, is studied. The sensors are fabricated by depositing chromium oxide films on a glass substrate using a modified spray pyrolysis technique and characterized using X-ray diffraction, scanning electron microscopy, transmission electron microscopy and X-ray photoelectron spectroscopy. The films are porous and nanocrystalline with an average crystallite size of similar to 30 nm. The typical p-type conductivity arises due to the presence of Cr vacancies, formed as a result of Cr non-stoichiometry, which is found to vary upon Pt doping. In order to analyze the effect of doping on the gas sensing properties, we have adopted a kinetic response analysis approach, which is based on Langmuir Adsorption isotherm (LA) theory. The sensor response is analyzed with equations obtained from LA theory and time constants as well as energies of adsorption-desorption are evaluated. It is seen that, Pt doping lowers the Schottky barrier height of the metal oxide semiconductor sensor from 222 meV to 172 meV. Subsequently the reduction in adsorption and desorption energies led to enhancement in sensor response and improvement in the kinetics of the sensor response i.e. the response time as well as recovery times of the sensor.

All Digital Energy Sensing for Minimum Energy Tracking

Minimizing energy consumption is of utmost importance in an energy starved system with relaxed performance requirements. This brief presents a digital energy sensing method that requires neither a constant voltage reference nor a time reference. An energy minimizing loop uses this to find the minimum energy point and sets the supply voltage between 0.2 and 0.5 V. Energy savings up to 1275% over existing minimum energy tracking techniques in the literature is achieved.

Synthesis of cadmium oxide and carbon nanotube based nanocomposites and their use as a sensing interface for xanthine detection

Xanthine oxidase (XOD) extracted from bovine milk was immobilized covalently via N-ethyl-N'-(3-dimethylaminopropyl) carbodiimide (EDC) and N-hydroxy succinimide (NHS) chemistry onto cadmium oxide nanoparticles (CdO)/carboxylated multiwalled carbon nanotube (c-MWCNT) composite film electrodeposited on the surface of an Au electrode. The nanocomposite modified Au electrode was characterized by Fourier transform infrared (FTIR), cyclic voltammetry (CV), scanning electron microscopy (SEM) and electrochemical impedance spectroscopy (EIS) before and after immobilization of XOD. Under optimal operation conditions (25 degrees C, + 0.2 V vs. Ag/AgCl, sodium phosphate buffer, pH 7.5), the following characteristics are attributed to the biosensor: linearity of response up to xanthine concentrations of 120 mu M, detection limit of 0.05 mu M (S/N = 3) and a response time of at most 4 s. After being used 100 times over a period of 120 days, only 50% loss of the initial activity of the biosensor was evaluated when stored at 4 degrees C. The fabricated biosensor was successfully employed for the determination of xanthine in fish meat.

Self-Assembled Discrete Molecules for Sensing Nitroaromatics

Efficient sensing of trace amount nitroaromatic (NAC) explosives has become a major research focus in recent time due to concerns over national security as well as their role as environment pollutants. NO2-containing electron-deficient aromatic compounds, such as picric acid (PA), trinitrotoluene (TNT), and dinitrotoluene (DNT), are the common constituents of many commercially available chemical explosives. In this article, we have summarized our recent developments on the rational design of electron-rich self-assembled discrete molecular sensors and their efficacy in sensing nitroaromatics both in solution as well as in vapor phase. Several p-electron-rich fluorescent metallacycles (squares, rectangles, and tweezers/pincers) and metallacages (trigonal and tetragonal prisms) have been synthesized by means of metal-ligand coordination-bonding interactions, with enough internal space to accommodate electron-deficient nitroaromatics at the molecular level by multiple supramolecular interactions. Such interactions subsequently result in the detectable fluorescence quenching of sensors even in the presence of trace quantities of nitroaromatics. The fascinating sensing characteristics of molecular architectures discussed in this article may enable future development of improved sensors for nitroaromatic explosives.

Correlation between band propagation property and the nature of serrations in the Portevin-Le Chatelier effect

We investigate the correlation between the band propagation property and the nature and amplitude of serrations in the Portevin-Le Chatelier effect within the framework of the Ananthakrishna model. Several significant results emerge. First, we find that spatial and temporal correlations continuously increase with strain rate from type C to type A bands. Consequently, the nature of the bands also changes continuously from type C to A bands, and so do the changes in the associated serrations. Second, even the smallest extent of propagation induces small amplitude serrations. The spatial extent of band propagation is directly correlated with the duration of small amplitude serrations, a result that is consistent with recent experiments. This correspondence allows one to estimate the spatial extent of band propagation by just measuring the temporal stretch of small amplitude serrations. Therefore, this should be of practical value when only stress versus strain is recorded. Third, the average stress drop magnitude of the small amplitude serrations induced by the propagating bands remains small and nearly constant with strain rate. As a consequence, the fully propagating type A bands are in a state of criticality. We rationalize the increasing levels of spatial and temporal correlations found with increasing strain rates. Lastly, the model also predicts several band morphologies seen in experiments including the Luders-like propagating band. (C) 2015 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Prediction of Land Surface Temperature under Cloudy Conditions using Microwave Remote Sensing and ANN

Land surface temperature (LST) is an important variable in climate, hydrologic, ecological, biophysical and biochemical studies (Mildrexler et al., 2011). The most effective way to obtain LST measurements is through satellites. Presently, LST from moderate resolution imaging spectroradiometer (MODIS) sensor is applied in various fields due to its high spatial and temporal availability over the globe, but quite difficult to provide observations in cloudy conditions. This study evolves of prediction of LST under clear and cloudy conditions using microwave vegetation indices (MVIs), elevation, latitude, longitude and Julian day as inputs employing an artificial neural network (ANN) model. MVIs can be obtained even under cloudy condition, since microwave radiation has an ability to penetrate through clouds. In this study LST and MVIs data of the year 2010 for the Cauvery basin on a daily basis were obtained from MODIS and advanced microwave scanning radiometer (AMSR-E) sensors of aqua satellite respectively. Separate ANN models were trained and tested for the grid cells for which both LST and MVI were available. The performance of the models was evaluated based on standard evaluation measures. The best performing model was used to predict LST where MVIs were available. Results revealed that predictions of LST using ANN are in good agreement with the observed values. The ANN approach presented in this study promises to be useful for predicting LST using satellite observations even in cloudy conditions. (C) 2015 The Authors. Published by Elsevier B.V.

Panchromatic Borane-aza-BODIPY Conjugate: Synthesis, Intriguing Optical Properties, and Selective Fluorescent Sensing of Fluoride Anions

A new triarylborane-aza-BODIPY conjugate is reported. The compound consists of two blue emissive dimesitylarylborane moieties and a near-infrared (NIR) emissive aza-BOIDPY core and shows panchromatic absorption spanning approximately 300-800 nm. DFT computational studies suggest limited electronic communication between the individual fluorophore units. Hence, the partial energy transfer from blue fluorophore triarylborane to NIR chromophore aza-BODIPY unit leads to a broad dual-emissive feature covering a large part of visible and NIR region. Furthermore, the broadband emissive compound can act as a selective sensor for fluoride anion as a result of fluorescence quenching response in both visible and NIR spectral regions.

Estimation of Aboveground Phytomass of Plantations Using Digital Photogrammetry and High Resolution Remote Sensing Data

The study follows an approach to estimate phytomass using recent techniques of remote sensing and digital photogrammetry. It involved tree inventory of forest plantations in Bhakra forest range of Nainital district. Panchromatic stereo dataset of Cartosat-1 was evaluated for mean stand height retrieval. Texture analysis and tree-tops detection analyses were done on Quick-Bird PAN data. The composite texture image of mean, variance and contrast with a 5x5 pixel window was found best to separate tree crowns for assessment of crown areas. Tree tops count obtained by local maxima filtering was found to be 83.4 % efficient with an RMSE+/-13 for 35 sample plots. The predicted phytomass ranged from 27.01 to 35.08 t/ha in the case of Eucalyptus sp. while in the case of Tectona grandis from 26.52 to 156 t/ha. The correlation between observed and predicted phytomass in Eucalyptus sp. was 0.468 with an RMSE of 5.12. However, the phytomass predicted in Tectona grandis was fairly strong with R-2=0.65 and RMSE of 9.89 as there was no undergrowth and the crowns were clearly visible. Results of the study show the potential of Cartosat-1 derived DSM and Quick-Bird texture image for the estimation of stand height, stem diameter, tree count and phytomass of important timber species.

A 0.5-2.0 GHz injection locked oscillator cascade for parallel wideband RF spectrum sensing

An area-efficient, wideband RF frequency synthesizer, which simultaneously generates multiple local oscillator (LO) signals, is designed. It is suitable for parallel wideband RF spectrum sensing in cognitive radios. The frequency synthesizer consists of an injection locked oscillator cascade (ILOC) where all the LO signals are derived from a single reference oscillator. The ILOC is implemented in a 130-nm technology with an active area of . It generates 4 uniformly spaced LO carrier frequencies from 500 MHz to 2 GHz. This design is the first known implementation of a CMOS based ILOC for wide-band RF spectrum sensing applications.

Zero-Crossings Based Spectrum Sensing Under Noise Uncertainties

In this work, the hypothesis testing problem of spectrum sensing in a cognitive radio is formulated as a Goodness-of-fit test against the general class of noise distributions used in most communications-related applications. A simple, general, and powerful spectrum sensing technique based on the number of weighted zero-crossings in the observations is proposed. For the cases of uniform and exponential weights, an expression for computing the near-optimal detection threshold that meets a given false alarm probability constraint is obtained. The proposed detector is shown to be robust to two commonly encountered types of noise uncertainties, namely, the noise model uncertainty, where the PDF of the noise process is not completely known, and the noise parameter uncertainty, where the parameters associated with the noise PDF are either partially or completely unknown. Simulation results validate our analysis, and illustrate the performance benefits of the proposed technique relative to existing methods, especially in the low SNR regime and in the presence of noise uncertainties.