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.

High-Temperature Deformation Processing Map Approach for Obtaining the Desired Microstructure in a Multi-component (Ni-Ti-Cu-Fe) Alloy

An equiatomic NiTiCuFe multi-component alloy with simple body-centered cubic (bcc) and face-centered cubic solid-solution phases in the microstructure was processed by vacuum induction melting furnace under dynamic Ar atmosphere. High-temperature uniaxial compression experiments were conducted on it in the temperature range of 1073 K to 1303 K (800 degrees C to 1030 degrees C) and strain rate range of 10(-3) to 10(-1) s(-1). The data generated were analyzed with the aid of the dynamic materials model through which power dissipation efficiency and instability maps were generated so as to identify the governing deformation mechanisms that are operative in different temperature-strain rate regimes with the aid of complementary microstructural analysis of the deformed specimens. Results indicate that the stable domain for the high temperature deformation of the multi-component alloy occurs in the temperature range of 1173 K to 1303 K (900 degrees C to 1030 degrees C) and (epsilon) over dot range of 10(-3) to 10(-1.2) s(-1), and the deformation is unstable at T = 1073 K to 1153 K (800 degrees C to 880 degrees C) and (epsilon) over dot = 10(-3) to 10(-1.4) s(-1) as well as T = 1223 K to 1293 K (950 degrees C to 1020 degrees C) and (epsilon) over dot = 10(-1.4) to 10(-1) s(-1), with adiabatic shear banding, localized plastic flow, or cracking being the unstable mechanisms. A constitutive equation that describes the flow stress of NiTiCuFe multi-component alloy as a function of strain rate and deformation temperature was also determined. (C) The Minerals, Metals & Materials Society and ASM International 2015

Imaging cellular signalling: many `moving tales' in MAP kinase odyssey

Cellular signalling events are at the core of every adaptive response. Signalling events link environmental changes to physiological responses, consequently allowing cellular and organismal sustenance and survival. Classical approaches to study cellular signalling have relied on a variety of cell disruptive techniques which yield limited kinetic information, while the underlying events are much more complex. In this article, we discuss how modern live cell imaging microscopy has found increasing utilization in revealing spatio temporal dynamics of various signalling pathways. Utilizing the well studied mitogen-activated protein kinase (MAPK) signalling cascade as a template, the design, construction and utilization of `mobile' (translocation proficient) biosensors, suitable for studying MAPK signalling in living cells are described in detail. Experimental setup and results obtained from these biosensors, based on different proteins involved in the MAPK signalling cascade, have been described along with the setup of a microscope optimal for live cell imaging applications. Utilizing the ability to activate or deactivate signalling pathways using defined activators and specific pharmacological inhibitors, we also show how these sensors can yield unique spatial and temporal kinetic information of signalling in living cells.

Seismic intensity map of South India for estimated future earthquakes

In this study, an attempt has been made to prepare the seismic intensity map for south India considering the probable earthquakes in the region. Anbazhagan et al. (Nat Hazards 60:1325-1345, 2012) have identified eight probable future earthquake zones in south India based on rupture-based seismic hazard analysis. Anbazhagan et al. (Eng Geol 171:81-95, 2014) has estimated the maximum future earthquake magnitude at these eight zones using regional rupture character. In this study, the whole south India is divided into several grids of size 1(o) x 1(o) and the intensity at each grid point is calculated using the regional intensity model for the maximum earthquake magnitude at each of the eight zones. The intensity due to earthquakes at these zones is mapped and thus eight seismic intensity maps are prepared. The final seismic intensity map of south India is obtained by considering the maximum intensity at each grid point due to the estimated earthquakes. By looking at the seismic intensity map, one can expect slight to heavy damage due to the probable earthquake magnitudes. Heavy damage may happen close to the probable earthquake zones.

Photometric metallicity map of the Large Magellanic Cloud

We have estimated a metallicity map of the Large Magellanic Cloud (LMC) using the Magellanic Cloud Photometric Survey (MCPS) and Optical Gravitational Lensing Experiment (OGLE III) photometric data. This is a first of its kind map of metallicity up to a radius of 4 degrees-5 degrees, derived using photometric data and calibrated using spectroscopic data of Red Giant Branch (RGB) stars. We identify the RGB in the V, (V - I) colour-magnitude diagrams of small subregions of varying sizes in both data sets. We use the slope of the RGB as an indicator of the average metallicity of a subregion, and calibrate the RGB slope to metallicity using spectroscopic data for field and cluster red giants in selected subregions. The average metallicity of the LMC is found to be Fe/H] = -0.37 dex (sigmaFe/H] = 0.12) from MCPS data, and Fe/H] = -0.39 dex (sigmaFe/H] = 0.10) from OGLE III data. The bar is found to be the most metal-rich region of the LMC. Both the data sets suggest a shallow radial metallicity gradient up to a radius of 4 kpc (-0.049 +/- 0.002 dex kpc(-1) to -0.066 +/- 0.006 dex kpc(-1)). Subregions in which the mean metallicity differs from the surrounding areas do not appear to correlate with previously known features; spectroscopic studies are required in order to assess their physical significance.

Spatio-temporal Map Formation Based on a Potential Function

We revisit the problem of temporal self organization using activity diffusion based on the neural gas (NGAS) algorithm. Using a potential function formulation motivated by a spatio-temporal metric, we derive an adaptation rule for dynamic vector quantization of data. Simulations results show that our algorithm learns the input distribution and time correlation much faster compared to the static neural gas method over the same data sequence under similar training conditions.

Visualisation of charge-transfer excitations in donor-acceptor molecules using the particle-hole map: a case study

Charge-transfer (CT) excitations are essential for photovoltaic phenomena in organic solar cells. Owing to the complexity of molecular geometries and orbital coupling, a detailed analysis and spatial visualisation of CT processes can be challenging. In this paper, a new detail-oriented visualisation scheme, the particle-hole map (PHM), is applied and explained for the purpose of spatial analysis of excitations in organic molecules. The PHM can be obtained from the output of a time-dependent density-functional theory calculation with negligible additional computational cost, and provides a useful physical picture for understanding the origins and destinations of electrons and holes during an excitation process. As an example, we consider intramolecular CT excitations in Diketopyrrolopyrrole-based molecules, and relate our findings to experimental results.