Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

Power sector development in India with CO2 emission targets: Effects of regional grid integration and the role of clean technologies

The power sector in India at present comprises of five separate regional electricity grids having practically no integrated operation in between them. This study analyses the utility planning, environmental and economical effects of integrated power sector development at the national level in which the regional electric grids are developed and operated as one integrated system. It also examines the effects of selected CO₂ emission reduction targets in the power sector and the role of renewable power generation technologies in India. The study shows that the integrated development and operation of the power system at the national level would reduce the total cost including fuel cost by 4912 million $, total capacity addition by 2784 MW, while the emission of CO₂, SO₂ and NO_x would be reduced by 231.6 (1.9%), 0.8 (0.9%), 0.4 (1.2%) million tons, respectively, during the planning horizon. Furthermore, the study shows that the expected unserved energy, one of the indices of generation system reliability, would decrease to 26 GWh under integrated national power system from 5158 GWh. As different levels of CO₂ emission reduction targets were imposed, there is a switching of generation from conventional coal plants to gas fired plants, clean coal technologies and nuclear based plants. As a result the capacity expansion cost has increased. It was found that wind power plant is most attractive and economical in the Indian perspective among the renewable options considered (Solar, wind and biomass). Copyright © 2003 John Wiley & Sons, Ltd.     

A new technique for on-line and off-line high speed computation

A novel technique for both online and offline computation is presented. With this technique, a reconstruction analysis in elementary particle physics, otherwise prohibitively long, has been accomplished. It will be used online in an upcoming Fermilab experiment to reconstruct more than 100000 events per second and to trigger on the basis of that information. The technique delivers 40 gigaoperations per second, has a bandwidth on the order of gigabytes per second, and has a modest cost. An overview of the program, details of the system, and performance measurements are presented     

Near-field optical imaging of unstained bacteria: comparison with normal atomic force and far-field optical microscopy in air and aqueous media

Simultaneous near-field scanning optical and atomic force imaging of bacteria is presented. The bacteria imaged in these studies were unstained. The near-field optical images had excellent signal-to-noise and showed excellent contrast even in these unstained specimens. The images obtained were interpreted in terms of the images that have been obtained by transmission electron microscopy and X-ray imaging. The results show that bacterial near-field optical imaging is going to be a very important tool in the arsenal of the bacteriologist both in terms of understanding the fundamental processes in the life cycle of bacteria with and without cytochemical staining and in terms of clinical diagnostic applications.     

A negative association of schizophrenia with an allele of the HLA DQB1 gene among African-Americans

The present study investigated the relationship between the time of nocturnal onset of urinary 6-sulfatoxymelatonin (aMT6s) secretion, and the timing of the steepest increase in nocturnal sleepiness ("sleep gate"), as determined by an ultrashort sleep-wake cycle test (7 min sleep, 13 min wake). Twenty-nine men (mean age 23.8 +/- 2.7 years) participated. The ultrashort sleep-wake paradigm started at 0700 hr after a night of sleep deprivation and continued for 24 hr until 0700 hr the next day. Electrophysiological recordings were carried out during the 7-min sleep trials, which were then scored conventionally for sleep stages. Urinary aMT6s was measured every 2 hr. The results showed that the timing of the sleep gate was significantly correlated with the onset of aMT6s secretion. These results are discussed in light of the possible role of melatonin in sleep-wake regulation.     

High‐order Higdon‐like boundary conditions for exterior transient wave problems

Recently developed non‐reflecting boundary conditions are applied for exterior time‐dependent wave problems in unbounded domains. The linear time‐dependent wave equation, with or without a dispersive term, is considered in an infinite domain. The infinite domain is truncated via an artificial boundary ??, and a high‐order non‐reflecting boundary condition (NRBC) is imposed on ??. Then the problem is solved numerically in the finite domain bounded by ??. The new boundary scheme is based on a reformulation of the sequence of NRBCs proposed by Higdon. We consider here two reformulations: one that involves high‐order derivatives with a special discretization scheme, and another that does not involve any high derivatives beyond second order. The latter formulation is made possible by introducing special auxiliary variables on ??. In both formulations the new NRBCs can easily be used up to any desired order. They can be incorporated in a finite element or a finite difference scheme; in the present paper the latter is used. In contrast to previous papers using similar formulations, here the method is applied to a fully exterior two‐dimensional problem, with a rectangular boundary. Numerical examples in infinite domains are used to demonstrate the performance and advantages of the new method. In the auxiliary‐variable formulation long‐time corner instability is observed, that requires special treatment of the corners (not addressed in this paper). No such difficulties arise in the high‐derivative formulation. Published in 2005 by John Wiley & Sons, Ltd.     

Enzymatic synthesis of sugar esters and their potential as surface-active stabilizers of coconut milk emulsions

Sugar esters are compounds with surfactant properties (biosurfactants), i.e., capable of reducing the surface tension and promote the emulsification of immiscible liquids. On the other hand, as with all emulsions, coconut milk is not physically stable and is prone to phase separation. Therefore, the aim of this work was to evaluate the synthesis of fructose, sucrose and lactose esters from the corresponding sugars using Candida antarctica type B lipase immobilized in two different supports, namely acrylic resin and chitosan, and evaluate its application in the stabilization of coconut milk emulsions. The enzyme immobilized on chitosan showed the highest yield of lactose ester production (84.1%). Additionally, the production of fructose ester was found to be higher for the enzyme immobilized on the acrylic resin support (74.3%) as compared with the one immobilized on chitosan (70.1%). The same trend was observed for the sucrose ester, although with lower percentage yields. Sugar esters were then added to samples of fresh coconut milk and characterized according to their surface tension, emulsification index and particle size distribution. Although the microscopic analysis showed similar results for all sugar esters, results indicated lactose ester as the best biosurfactant, with a surface tension of 38.0 N/m and an emulsification index of 54.1%, when used in a ratio of 1:10 (biosurfactant:coconut milk, v/v) for 48 h experiments.     

On Demand Solid Texture Synthesis Using Deep 3D Networks

This paper describes a novel approach for on demand volumetric texture synthesis based on a deep learning framework that allows for the generation of high-quality three-dimensional (3D) data at interactive rates. Based on a few example images of textures, a generative network is trained to synthesize coherent portions of solid textures of arbitrary sizes that reproduce the visual characteristics of the examples along some directions. To cope with memory limitations and computation complexity that are inherent to both high resolution and 3D processing on the GPU, only 2D textures referred to as ‘slices’ are generated during the training stage. These synthetic textures are compared to exemplar images via a perceptual loss function based on a pre-trained deep network. The proposed network is very light (less than 100k parameters), therefore it only requires sustainable training (i.e. few hours) and is capable of very fast generation (around a second for 256³ voxels) on a single GPU. Integrated with a spatially seeded pseudo-random number generator (PRNG) the proposed generator network directly returns a color value given a set of 3D coordinates. The synthesized volumes have good visual results that are at least equivalent to the state-of-the-art patch-based approaches. They are naturally seamlessly tileable and can be fully generated in parallel.