Indian Institute of Technology Bombay

About: Indian Institute of Technology Bombay is a education organization based out in Mumbai, India. It is known for research contribution in the topics: Catalysis & Computer science. The organization has 16756 authors who have published 33588 publications receiving 570559 citations.

Multiparticle azimuthal correlations in p -Pb and Pb-Pb collisions at the CERN Large Hadron Collider

Abstract: Measurements of multiparticle azimuthal correlations (cumulants) for charged particles in p-Pb at √sNN√=5.02 TeV and Pb-Pb at √sNN=2.76 TeV collisions are presented. They help address the question of whether there is evidence for global, flowlike, azimuthal correlations in the p-Pb system. Comparisons are made to measurements from the larger Pb-Pb system, where such evidence is established. In particular, the second harmonic two-particle cumulants are found to decrease with multiplicity, characteristic of a dominance of few-particle correlations in p-Pb collisions. However, when a |Δη| gap is placed to suppress such correlations, the two-particle cumulants begin to rise at high multiplicity, indicating the presence of global azimuthal correlations. The Pb-Pb values are higher than the p-Pb values at similar multiplicities. In both systems, the second harmonic four-particle cumulants exhibit a transition from positive to negative values when the multiplicity increases. The negative values allow for a measurement of v2{4} to be made, which is found to be higher in Pb-Pb collisions at similar multiplicities. The second harmonic six-particle cumulants are also found to be higher in Pb-Pb collisions. In Pb-Pb collisions, we generally find v2{4}≃v2{6}≠0 which is indicative of a Bessel-Gaussian function for the v2 distribution. For very high-multiplicity Pb-Pb collisions, we observe that the four- and six-particle cumulants become consistent with 0. Finally, third harmonic two-particle cumulants in p-Pb and Pb-Pb are measured. These are found to be similar for overlapping multiplicities, when a |Δη|>1.4 gap is placed.

Impacts of land use–land cover change and urbanization on flooding: A case study of Oshiwara River Basin in Mumbai, India

Abstract: In the present study, the impact of land use–land cover (LULC) change and urbanization on floods are investigated for an expanding urban catchment of the Oshiwara River in Mumbai, India. For the study area, the land use change was estimated between 1966, 2001 and 2009 by using the topographic map and satellite images. The analysis of LULC change revealed that the change between 1966 and 2001 was slower than that between 2001 and 2009. The LULC analysis revealed a 74.84% increase in the built up area with a 42.8% decrease in open spaces between the years 1966 and 2009, with substantial increase in urbanization. The impact of LULC on flood hydrograph for different return periods was ascertained by using the HEC-GeoHMS and HEC-HMS models. In the past 43 years, the increase in peak runoff and runoff volume is marginally varied by 3.0% and 4.45% for the 100-year return period and 10.4% and 12.2% for the 2-year return period respectively, although the built-up area increased by 74.84%. The flood inundation area is increased by 5.61% for the 100-year return period and 6.04% for the 10-year return period between the same time period. The results showed that lower return periods led to a maximum change in peak discharge/volume of runoff compared to higher return periods for change in land use conditions. Further, a flood hazard analysis has been carried out and it showed that the area in highly hazardous zone is increased by 64.29% as compared to less hazardous zone where it is decreased by 32.14%. Overall, the total flood hazard area is increased by 22.27%. The developed flood plain and flood hazard maps can be used by the local Municipal body to prepare flood mitigation and early evacuation management plans during floods and as a criteria for insurance of any property by insurance organizations.

Nanomaterials: amyloids reflect their brighter side

Abstract: Amyloid fibrils belong to the group of ordered nanostructures that are self-assembled from a wide range of polypeptides/ proteins. Amyloids are highly rigid structures possessing a high mechanical strength. Although amyloids have been implicated in the pathogenesis of several human diseases, growing evidence indicates that amyloids may also perform native functions in host organisms. Discovery of such amyloids, referred to as functional amyloids, highlight their possible use in designing novel nanostructure materials. This review summarizes recent advances in the application of amyloids for the development of nanomaterials and prospective applications of such materials in nanotechnology and biomedicine. Keywords: Nanotechnology; self-assembly; peptide/protein; fibrils; tissue engineering; stem cells; drug delivery; nanowires (Published: 31 May 2011) Citation: Nano Reviews 2011, 2 : 6032 - DOI: 10.3402/nano.v2i0.6032

MPPT Scheme for a PV-Fed Single-Phase Single-Stage Grid-Connected Inverter Operating in CCM With Only One Current Sensor

Abstract: The cost and efficiency of a photovoltaic (PV)-based grid-connected system depends upon the number of components and stages involved in the power conversion. This has led to the development of several single-stage configurations that can perform voltage transformation, maximum power point tracking (MPPT), inversion, and current shaping-all in one stage. Such configurations would usually require at least a couple of current and voltage sensors and a relatively complex control strategy. With a view to minimize the overall cost and control complexity, this paper presents a novel MPPT scheme with reduced number of sensors. The proposed scheme is applicable to any single-stage, single-phase grid-connected inverter operating in continuous conduction mode (CCM). The operation in CCM is desirable as it drastically reduces the stress on the components. Unlike other MPPT methods, which sense both PV array's output current and voltage, only PV array's output voltage is required to be sensed to implement MPPT. Only one current sensor is used for shaping the buck-boost inductor current as well as for MPPT. The information about power output of the array is obtained indirectly from array's voltage and the inductor current amplitude. Detailed analysis and the flowchart of the algorithm for the proposed scheme are included. Simulation and experimental results are also presented to highlight the usefulness of the scheme.

Learning Local Shape Descriptors from Part Correspondences with Multiview Convolutional Networks

Abstract: We present a new local descriptor for 3D shapes, directly applicable to a wide range of shape analysis problems such as point correspondences, semantic segmentation, affordance prediction, and shape-to-scan matching. The descriptor is produced by a convolutional network that is trained to embed geometrically and semantically similar points close to one another in descriptor space. The network processes surface neighborhoods around points on a shape that are captured at multiple scales by a succession of progressively zoomed-out views, taken from carefully selected camera positions. We leverage two extremely large sources of data to train our network. First, since our network processes rendered views in the form of 2D images, we repurpose architectures pretrained on massive image datasets. Second, we automatically generate a synthetic dense point correspondence dataset by nonrigid alignment of corresponding shape parts in a large collection of segmented 3D models. As a result of these design choices, our network effectively encodes multiscale local context and fine-grained surface detail. Our network can be trained to produce either category-specific descriptors or more generic descriptors by learning from multiple shape categories. Once trained, at test time, the network extracts local descriptors for shapes without requiring any part segmentation as input. Our method can produce effective local descriptors even for shapes whose category is unknown or different from the ones used while training. We demonstrate through several experiments that our learned local descriptors are more discriminative compared to state-of-the-art alternatives and are effective in a variety of shape analysis applications.