Influence of system size on spatiotemporal dynamics of a model for plastic instability: Projecting low-dimensional and extensive chaos

This work is a continuation of our efforts to quantify the irregular scalar stress signals from the Ananthakrishna model for the Portevin-Le Chatelier instability observed under constant strain rate deformation conditions. Stress related to the spatial average of the dislocation activity is a dynamical variable that also determines the time evolution of dislocation densities. We carry out detailed investigations on the nature of spatiotemporal patterns of the model realized in the form of different types of dislocation bands seen in the entire instability domain and establish their connection to the nature of stress serrations. We then characterize the spatiotemporal dynamics of the model equations by computing the Lyapunov dimension as a function of the drive parameter. The latter scales with the system size only for low strain rates, where isolated dislocation bands are seen, and at high strain rates, where fully propagating bands are seen. At intermediate applied strain rates corresponding to the partially propagating bands, the Lyapunov dimension exhibits two distinct slopes, one for small system sizes and another for large. This feature is rationalized by demonstrating that the spatiotemporal patterns for small system sizes are altered from the partially propagating band types to isolated burst type. This in turn allows us to reconfirm that low-dimensional chaos is projected from the stress signals as long as there is a one-to-one correspondence between the bursts of dislocation bands and the stress drops. We then show that the stress signals in the regime of partially to fully propagative bands have features of extensive chaos by calculating the correlation dimension density. We also show that the correlation dimension density also depends on the system size. A number of issues related to the system size dependence of the Lyapunov dimension density and the correlation dimension density are discussed.

Fluctuations in the alpha-effect and grand solar minima

The parameters of a special type of alpha-effect known in dynamo theory as the Babcock-Leighton mechanism are estimated using the data of sunspot catalogs. The estimates support the presence of the Babcock-Leighton alpha-effect on the Sun. Fluctuations of the alpha-effect are also estimated. The fluctuation amplitude appreciably exceeds themean value, and the characteristic time for the fluctuations is comparable to the period of the solar rotation. Fluctuations with the parameters found are included in a numericalmodel for the solar dynamo. Computations show irregular changes in the amplitudes of the magnetic cycles on time scales of centuries and millennia. The calculated statistical characteristics of the grand solar minima and maxima agree with the data on solar activity over the Holocene.

Remote sensing applications in water resources

With the introduction of the earth observing satellites, remote sensing has become an important tool in analyzing the Earth's surface characteristics, and hence in supplying valuable information necessary for the hydrologic analysis. Due to their capability to capture the spatial variations in the hydro-meteorological variables and frequent temporal resolution sufficient to represent the dynamics of the hydrologic processes, remote sensing techniques have significantly changed the water resources assessment and management methodologies. Remote sensing techniques have been widely used to delineate the surface water bodies, estimate meteorological variables like temperature and precipitation, estimate hydrological state variables like soil moisture and land surface characteristics, and to estimate fluxes such as evapotranspiration. Today, near-real time monitoring of flood, drought events, and irrigation management are possible with the help of high resolution satellite data. This paper gives a brief overview of the potential applications of remote sensing in water resources.

Analysis of large-amplitude stratospheric mountain wave event observed from the AIRS and MLS sounders over the western Himalayan region

Mountain waves in the stratosphere have been observed over elevated topographies using both nadir-looking and limb-viewing satellites. However, the characteristics of mountain waves generated over the Himalayan Mountain range and the adjacent Tibetan Plateau are relatively less explored. The present study reports on three-dimensional (3-D) properties of a mountain wave event that occurred over the western Himalayan region on 9 December 2008. Observations made by the Atmospheric Infrared Sounder on board the Aqua and Microwave Limb Sounder on board the Aura satellites are used to delineate the wave properties. The observed wave properties such as horizontal (lambda(x), lambda(y)) and vertical (lambda(z)) wavelengths are 276 km (zonal), 289 km (meridional), and 25 km, respectively. A good agreement is found between the observed and modeled/analyzed vertical wavelength for a stationary gravity wave determined using the Modern Era Retrospective Analysis for Research and Applications (MERRA) reanalysis winds. The analysis of both the National Centers for Environmental Prediction/National Center for Atmospheric Research reanalysis and MERRA winds shows that the waves are primarily forced by strong flow across the topography. Using the 3-D properties of waves and the corrected temperature amplitudes, we estimated wave momentum fluxes of the order of similar to 0.05 Pa, which is in agreement with large-amplitude mountain wave events reported elsewhere. In this regard, the present study is considered to be very much informative to the gravity wave drag schemes employed in current general circulation models for this region.

Constraining complex aquifer geometry with geophysics (2-D ERT and MRS measurements) for stochastic modelling of groundwater flow

Stochastic modelling is a useful way of simulating complex hard-rock aquifers as hydrological properties (permeability, porosity etc.) can be described using random variables with known statistics. However, very few studies have assessed the influence of topological uncertainty (i.e. the variability of thickness of conductive zones in the aquifer), probably because it is not easy to retrieve accurate statistics of the aquifer geometry, especially in hard rock context. In this paper, we assessed the potential of using geophysical surveys to describe the geometry of a hard rock-aquifer in a stochastic modelling framework. The study site was a small experimental watershed in South India, where the aquifer consisted of a clayey to loamy-sandy zone (regolith) underlain by a conductive fissured rock layer (protolith) and the unweathered gneiss (bedrock) at the bottom. The spatial variability of the thickness of the regolith and fissured layers was estimated by electrical resistivity tomography (ERT) profiles, which were performed along a few cross sections in the watershed. For stochastic analysis using Monte Carlo simulation, the generated random layer thickness was made conditional to the available data from the geophysics. In order to simulate steady state flow in the irregular domain with variable geometry, we used an isoparametric finite element method to discretize the flow equation over an unstructured grid with irregular hexahedral elements. The results indicated that the spatial variability of the layer thickness had a significant effect on reducing the simulated effective steady seepage flux and that using the conditional simulations reduced the uncertainty of the simulated seepage flux. As a conclusion, combining information on the aquifer geometry obtained from geophysical surveys with stochastic modelling is a promising methodology to improve the simulation of groundwater flow in complex hard-rock aquifers. (C) 2013 Elsevier B.V. All rights reserved.

Hydrothermal synthesis of Gd2O3:Eu3+ nanophosphors: Effect of surfactant on structural and luminescence properties

Various morphologies of Eu3+ activated gadolinium oxide have been prepared by hydrothermal method using hexadecylamine (HDA) as surfactant at different experimental conditions. The powder X-ray diffraction studies reveal as-formed product is hexagonal Gd(OH)(3):Eu3+ phase and subsequent heat treatment at 350 and 600 degrees C transforms to monoclinic GdOOH:Eu3+ and cubic Gd2O3:Eu3+ phases respectively. SEM pictures of without surfactant show irregular shaped rods along with flakes. However, in the presence of HDA surfactant, the particles are converted into rods of various sizes. The temperature dependent morphological evolution of Gd2O3:Eu3+ without and with HDA surfactant is studied. TEM micrographs of Gd(OH)(3):Eu3+ sample with HDA confirms smooth nanorods with various diameters in the range 20-100 nm. FTIR studies reveal that HDA surfactant plays an important role in conversion of cubic to hexagonal phases. Among these three phases, cubic phase Gd2O3:Eu3+ (lambda(ex) = 254 nm) show red emission at 612 nm corresponding to D-5(0)-> F-7(2) and is more efficient host than the monoclinic counterpart. The band gap for hexagonal Gd(OH)(3):Eu3+ is more when compared to monoclinic GdOOH:Eu3+ and cubic Gd2O3:Eu3+. (C) 2013 Elsevier B. V. All rights reserved.

A simple model for spatial disaggregation of evaporative fraction: Comparative study with thermal sharpened land surface temperature data over India

[1] Evaporative fraction (EF) is a measure of the amount of available energy at the earth surface that is partitioned into latent heat flux. The currently operational thermal sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) on satellite platforms provide data only at 1000 m, which constraints the spatial resolution of EF estimates. A simple model (disaggregation of evaporative fraction (DEFrac)) based on the observed relationship between EF and the normalized difference vegetation index is proposed to spatially disaggregate EF. The DEFrac model was tested with EF estimated from the triangle method using 113 clear sky data sets from the MODIS sensor aboard Terra and Aqua satellites. Validation was done using the data at four micrometeorological tower sites across varied agro-climatic zones possessing different land cover conditions in India using Bowen ratio energy balance method. The root-mean-square error (RMSE) of EF estimated at 1000 m resolution using the triangle method was 0.09 for all the four sites put together. The RMSE of DEFrac disaggregated EF was 0.09 for 250 m resolution. Two models of input disaggregation were also tried with thermal data sharpened using two thermal sharpening models DisTrad and TsHARP. The RMSE of disaggregated EF was 0.14 for both the input disaggregation models for 250 m resolution. Moreover, spatial analysis of disaggregation was performed using Landsat-7 (Enhanced Thematic Mapper) ETM+ data over four grids in India for contrasted seasons. It was observed that the DEFrac model performed better than the input disaggregation models under cropped conditions while they were marginally similar under non-cropped conditions.

Characterization and Space-Time Downscaling of the Inundation Extent over the Inner Niger Delta Using GIEMS and MODIS Data

The objective in this work is to develop downscaling methodologies to obtain a long time record of inundation extent at high spatial resolution based on the existing low spatial resolution results of the Global Inundation Extent from Multi-Satellites (GIEMS) dataset. In semiarid regions, high-spatial-resolution a priori information can be provided by visible and infrared observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). The study concentrates on the Inner Niger Delta where MODIS-derived inundation extent has been estimated at a 500-m resolution. The space-time variability is first analyzed using a principal component analysis (PCA). This is particularly effective to understand the inundation variability, interpolate in time, or fill in missing values. Two innovative methods are developed (linear regression and matrix inversion) both based on the PCA representation. These GIEMS downscaling techniques have been calibrated using the 500-m MODIS data. The downscaled fields show the expected space-time behaviors from MODIS. A 20-yr dataset of the inundation extent at 500 m is derived from this analysis for the Inner Niger Delta. The methods are very general and may be applied to many basins and to other variables than inundation, provided enough a priori high-spatial-resolution information is available. The derived high-spatial-resolution dataset will be used in the framework of the Surface Water Ocean Topography (SWOT) mission to develop and test the instrument simulator as well as to select the calibration validation sites (with high space-time inundation variability). In addition, once SWOT observations are available, the downscaled methodology will be calibrated on them in order to downscale the GIEMS datasets and to extend the SWOT benefits back in time to 1993.

Monte Carlo simulation of light transport in turbid medium with embedded object-spherical, cylindrical, ellipsoidal, or cuboidal objects embedded within multilayered tissues

Monte Carlo modeling of light transport in multilayered tissue (MCML) is modified to incorporate objects of various shapes (sphere, ellipsoid, cylinder, or cuboid) with a refractive-index mismatched boundary. These geometries would be useful for modeling lymph nodes, tumors, blood vessels, capillaries, bones, the head, and other body parts. Mesh-based Monte Carlo (MMC) has also been used to compare the results from the MCML with embedded objects (MCML-EO). Our simulation assumes a realistic tissue model and can also handle the transmission/reflection at the object-tissue boundary due to the mismatch of the refractive index. Simulation of MCML-EO takes a few seconds, whereas MMC takes nearly an hour for the same geometry and optical properties. Contour plots of fluence distribution from MCML-EO and MMC correlate well. This study assists one to decide on the tool to use for modeling light propagation in biological tissue with objects of regular shapes embedded in it. For irregular inhomogeneity in the model (tissue), MMC has to be used. If the embedded objects (inhomogeneity) are of regular geometry (shapes), then MCML-EO is a better option, as simulations like Raman scattering, fluorescent imaging, and optical coherence tomography are currently possible only with MCML. (C) 2014 Society of Photo-Optical Instrumentation Engineers (SPIE)

Evaluation of TRMM PR Sampling Error Over a Subtropical Basin Using Bootstrap Technique

Quantitative use of satellite-derived rainfall products for various scientific applications often requires them to be accompanied with an error estimate. Rainfall estimates inferred from low earth orbiting satellites like the Tropical Rainfall Measuring Mission (TRMM) will be subjected to sampling errors of nonnegligible proportions owing to the narrow swath of satellite sensors coupled with a lack of continuous coverage due to infrequent satellite visits. The authors investigate sampling uncertainty of seasonal rainfall estimates from the active sensor of TRMM, namely, Precipitation Radar (PR), based on 11 years of PR 2A25 data product over the Indian subcontinent. In this paper, a statistical bootstrap technique is investigated to estimate the relative sampling errors using the PR data themselves. Results verify power law scaling characteristics of relative sampling errors with respect to space-time scale of measurement. Sampling uncertainty estimates for mean seasonal rainfall were found to exhibit seasonal variations. To give a practical example of the implications of the bootstrap technique, PR relative sampling errors over a subtropical river basin of Mahanadi, India, are examined. Results reveal that the bootstrap technique incurs relative sampling errors < 33% (for the 2 degrees grid), < 36% (for the 1 degrees grid), < 45% (for the 0.5 degrees grid), and < 57% (for the 0.25 degrees grid). With respect to rainfall type, overall sampling uncertainty was found to be dominated by sampling uncertainty due to stratiform rainfall over the basin. The study compares resulting error estimates to those obtained from latin hypercube sampling. Based on this study, the authors conclude that the bootstrap approach can be successfully used for ascertaining relative sampling errors offered by TRMM-like satellites over gauged or ungauged basins lacking in situ validation data. This technique has wider implications for decision making before incorporating microwave orbital data products in basin-scale hydrologic modeling.

GdAlO3:Eu3+:Bi3+ nanophosphor: Synthesis and enhancement of red emission for WLEDs

GdAlO3, GdAlO3:Eu3+ and GdAlO3:Eu3+:Bi3+ nanophosphors were synthesised by solution combustion technique. Pure orthorhombic phase was obtained from powder X-ray diffraction (PXRD) studies. Scanning electron microscopy (SEM) micrographs showed the porous, agglomerated and irregular shaped particles. The particle size obtained by transmission electron microscopy (TEM) measurement was in good agreement with the values obtained by Debye Scherrer's and W-H plots. The selected area electron diffraction (SAED) pattern show single crystalline nature of the sample. Photoluminescence (PL) measurements were carried out for GdAlO3:Eu3+ and GdAlO3:Eu3+:Bi3+ phosphors excited at a wavelength of 274 nm. The characteristic emission peaks of Eu3+ ions were recorded at 590, 614, 655 and 695 nm corresponding to D-5(0) -> F-7(J) (J = 1, 2, 3, 4) transitions respectively. However, with addition of Bi3+ ions in GdAlO3:Eu3+, PL intensity drastically enhanced. Orange red color was tuned to deep red color with the addition of Bi3+ ions in GdAlO3:Eu3+ phosphor. Therefore, the phosphor was highly useful as red component in WLEDs. A single well resoled glow peak at 225 degrees C was recorded in GdAlO3 and GdAlO3:Eu3+. Further, with addition of Bi3+ ions, an additional peak at 300 degrees C was recorded. TL glow curves of different UV-exposed GdAlO3:Eu3+:Bi3+ show two TL peaks at 207 and 300 degrees C respectively. The 207 degrees C peak show simple glow peak structure and its intensity increases linearly up to 25 mm and after that it decrease. (C) 2014 Elsevier B.V. All rights reserved.

Synthesis and photoluminescence properties of a novel Sr2CeO4:Dy3+ nanophosphor with enhanced brightness by Li+ co-doping

A series of Dy3+ (0.5-9 mol%) and Li+ (0.5-3 mol%) co-doped strontium cerate (Sr2CeO4) nanopowders are synthesized by low temperature solution combustion synthesis. The effects of Li+ doping on the crystal structure, chemical composition, surface morphology and photoluminescence properties are investigated. The X-ray diffraction results confirm that all the samples calcined at 900 degrees C show the pure orthorhombic (Pbam) phase. Scanning electron microscopy analysis reveals that the particles adopt irregular morphology and the porous nature of the product. Room temperature photoluminescence results indicate that the phosphor can be effectively excited by near UV radiation (290 to 390 nm) which results in the blue (484 nm) and yellow (575 nm) emission. Furthermore, PL emission intensity and wavelength are highly dependent on the concentration of Li+ doping. The emission intensity is enhanced by similar to 3 fold with Li+ doping. White light is achieved by merely varying dopant concentration. The colour purity of the phosphor is confirmed by CIE co-ordinates (x = 0.298, y = 0.360). The study demonstrates a simple and efficient method for the synthesis of novel nanophosphors with enhanced white emission.

Impact dynamics of high Weber number drops on chemically modified metallic surfaces

Hydrophobic/superhydrophobic metallic surfaces prepared via chemical treatment are encountered in many industrial scenarios involving the impingement of spray droplets. The effectiveness of such surfaces is understood through the analysis of droplet impact experiments. In the present study, three target surfaces with aluminum (Al-6061) as base material-acid-etched, Octadecyl Trichloro Silane (OTS) coated, and acid-etched plus OTS-coated-were prepared. Experiments on the impact of inertia dominated water drops on these chemically modified aluminum surfaces were carried out with the objective to highlight the effect of chemical treatment on the target surfaces on key sub-processes occurring in drop impact phenomenon. High speed videos of the entire drop impact dynamics were captured at three Weber number (We) conditions representative of high We (We > 200) regime. During the early stages of drop spreading, the drop impact resulted in ejection of secondary droplets from spreading drop front on the etched surfaces resembling prompt splash on rough surfaces whereas no such splashing was observable on untreated aluminum surface. Prominent development of undulations (fingers) were observed at the rim of drop spreading on the etched surfaces; between the etched surfaces the OTS-coated surface showed a subdued development of fingers than the uncoated surface. The impacted drops showed intense receding on OTS-coated surfaces whereas on the etched surface a highly irregular receding, with drop liquid sticking to the surface, was observed. Quantitative analyses were performed to reveal the effect of target surface characteristics on drop impact parameters such as temporal variation of spread factor of drop lamella, temporal variation of average finger length during spreading phase, maximum drop spreading, time taken to attain maximum spreading, sensitivity of maximum spreading to We, number of fingers at maximum spreading, and average receding velocity of drop lamella. Existing models for maximum drop spreading showed reasonably good agreement with the experimental measurements on the target surfaces except the acid-etched surface. (C) 2014 Elsevier B.V. All rights reserved.

Channel Hardening-Exploiting Message Passing (CHEMP) Receiver in Large-Scale MIMO Systems

In this paper, we propose a multiple-input multiple-output (MIMO) receiver algorithm that exploits channel hardening that occurs in large MIMO channels. Channel hardening refers to the phenomenon where the off-diagonal terms of the matrix become increasingly weaker compared to the diagonal terms as the size of the channel gain matrix increases. Specifically, we propose a message passing detection (MPD) algorithm which works with the real-valued matched filtered received vector (whose signal term becomes, where is the transmitted vector), and uses a Gaussian approximation on the off-diagonal terms of the matrix. We also propose a simple estimation scheme which directly obtains an estimate of (instead of an estimate of), which is used as an effective channel estimate in the MPD algorithm. We refer to this receiver as the channel hardening-exploiting message passing (CHEMP) receiver. The proposed CHEMP receiver achieves very good performance in large-scaleMIMO systems (e.g., in systems with 16 to 128 uplink users and 128 base station antennas). For the considered large MIMO settings, the complexity of the proposed MPD algorithm is almost the same as or less than that of the minimum mean square error (MMSE) detection. This is because the MPD algorithm does not need a matrix inversion. It also achieves a significantly better performance compared to MMSE and other message passing detection algorithms using MMSE estimate of. Further, we design optimized irregular low density parity check (LDPC) codes specific to the considered large MIMO channel and the CHEMP receiver through EXIT chart matching. The LDPC codes thus obtained achieve improved coded bit error rate performance compared to off-the-shelf irregular LDPC codes.

Energy Efficient GPS Acquisition with Sparse-GPS

Following rising demands in positioning with GPS, low-cost receivers are becoming widely available; but their energy demands are still too high. For energy efficient GPS sensing in delay-tolerant applications, the possibility of offloading a few milliseconds of raw signal samples and leveraging the greater processing power of the cloud for obtaining a position fix is being actively investigated. In an attempt to reduce the energy cost of this data offloading operation, we propose Sparse-GPS(1): a new computing framework for GPS acquisition via sparse approximation. Within the framework, GPS signals can be efficiently compressed by random ensembles. The sparse acquisition information, pertaining to the visible satellites that are embedded within these limited measurements, can subsequently be recovered by our proposed representation dictionary. By extensive empirical evaluations, we demonstrate the acquisition quality and energy gains of Sparse-GPS. We show that it is twice as energy efficient than offloading uncompressed data, and has 5-10 times lower energy costs than standalone GPS; with a median positioning accuracy of 40 m.