(SoE) School of Engineering

<p>Shiv Nadar University is a comprehensive, multidisciplinary, research-focused, and student-centric University offering a full range of academic programs at the undergraduate, postgraduate and doctoral level. With state-of-the-art infrastructure, the University comprises of academic wings, sophisticated labs, international standard sports facilities, amphitheaters, auditorium, conference rooms and smart classrooms. The University&rsquo;s goal is to become internationally recognized for the quality of its research and creative endeavors and their applicability to improving quality of life, generating new insights and expanding the boundaries of human knowledge creativity. Committed to excellence in teaching, research and service, the University aims to serve the higher education needs of India and the world beyond.</p>

Shiv Nadar University

Toxic elements present in airborne particulate matter (PM) are associated with human health effects; however, their toxic characteristics depend on the source of their origins and their concentrations in ambient air. Twenty four elements (Al, B, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, Ga, K, Li, Mg, Mn, Na, Ni, Pb, Se, Sr, Te, Tl, and Zn) in 12 different size fractions of PM ranging from 10 nm to 10 μm were characterized in Singapore during two different atmospheric conditions (smoke haze and non-haze periods) in 2012 for the first time. In addition, their possible sources were identified based on backward air trajectory analysis and principal component analysis (PCA). The health implications of inhalable particles were assessed using a human airway deposition model, the Multiple-Path Particle Dosimetry model (MPPD). The results concerning particle-bound trace elements are interpreted in terms of coarse (PM2.5−10), fine (PM2.5), ultrafine (PM0.01−0.1, 0.01 μm &lt; Dp &lt; 0.10 μm), and nano (PM0.01−0.056, 0.01 μm &lt; Dp &lt; 0.056 μm) particles. The ratios of elemental concentrations measured between the smoke haze episode and the non-haze period in coarse, fine, ultrafine, and nano particles varied from 1.2 (Bi) to 6.6 (Co). Both the PCA and backward trajectory analysis revealed that trans-boundary biomass-burning emissions from Indonesia were primarily responsible for enhanced concentrations of particulate-bound elements during the smoke haze episode. The particle depositions in the respiratory system were higher during the smoke haze episode compared to the non-haze period. The study finds that ultrafine and nano particles present in the atmosphere have higher tendencies to be deposited into the deeper parts of the respiratory system, compared to coarse and fine particles. © 2014, Springer-Verlag Berlin Heidelberg.

Civil Engineering

World University root node

Environmental Science and Pollution Research

Characterization and estimation of human airway deposition of size-resolved particulate-bound trace elements during a recent haze episode in Southeast Asia

In this paper, we study the maximum density, threshold and emptiness queries for intervals in the streaming model. The input is a stream S of n points in the real line R and a floating closed interval W of width α. The specific problems we consider in this paper are as follows. Maximum density: find a placement of W in ℝ containing the maximum number of points of S. Threshold query: find a placement of W in R, if it exists, that contains at least Δ elements of S. Emptiness query: find, if possible, a placement of W within the extent of S so that the interior of W does not contain any element of S. The stream S, being huge, does not fit into main memory and can be read sequentially at most a constant number of times, usually once. The problems studied here in the geometric setting have relations to frequency estimation and heavy hitter identification in a stream of data. We provide lower bounds and results on trade-off between extra space and quality of solution. We also discuss generalizations for the higher dimensional variants for a few cases. © Arijit Bishnu, Amit Chakrabarti, Subhas C. Nandy, and Sandeep Sen;.

Leibniz International Proceedings in Informatics, LIPIcs

On density, threshold and emptiness queries for intervals in the streaming model

We present an algorithm for maintaining maximal matching in a graph under addition and deletion of edges. Our algorithm is randomized and it takes expected amortized O (log n ) time for each edge update, where n is the number of vertices in the graph. While there exists a trivial O (n) time algorithm for each edge update, the previous best known result for this problem is due to Ivković and Lloyd [Lecture Notes in Comput. Sci. 790, Springer-Verlag, London, 1994, pp. 99-111]. For a graph with n vertices and m edges, they gave an O ((n + m)0. 7072) update time algorithm which is sublinear only for a sparse graph. For the related problem of maximum matching, Onak and Rubinfeld [ Proceedings of STOC'10, Cambridge, MA, 2010, pp. 457-464] designed a randomized algorithm that achieves expected amortized O (log 2n) time for each update for maintaining a capproximate maximum matching for some unspecified large constant c . In contrast, we can maintain a factor 2 approximate maximum matching in expected amortized O (log n) time per update as a direct corollary of the maximal matching scheme. This in turn also implies a 2-approximate vertex cover maintenance scheme that takes expected amortized O (log n ) time per update. © 2015 Society for Industrial and Applied Mathematics.

Fulltext

SIAM Journal on Computing

Fully dynamic maximal matching in O(log n) update time

Chemical Engineering

Process Safety and Environmental Protection

Editorial

Superhydrophobicity facilitates the development of self-cleaning, anti-biofouling, and anti-corrosion surfaces. The leaves of the lotus (Nelumbo nucifera) and taro (Colocasia esculenta) plants are well known for their self-cleaning properties. A hierarchical structure comprising papillae epidermal cells superimposed with epicuticular wax crystalloids of varying shapes, sizes, and orientations is an important aspect of the surface of these plant leaves. We fabricated two types of hierarchical structures biomimicking the surface topography of the lotus leaf. The hierarchical patterns successfully demonstrated the superhydrophobic state in comparison with nano and micro patterns. We used the finite element method (FEM) to simulate and understand the wetting process. The FEM simulations showed good correlation with the experimental results. FEM was helpful in understanding the wetting of enormously complex biological surfaces with relative ease, and it qualifies as a potential tool for designing superhydrophobic surfaces. Using the FEM framework, we further designed surfaces to optimize the order of the shapes in hierarchy. The results showed that the superhydrophobic surface with the lowest wetted area was obtained by placing shapes with smaller geometric angles at the top of the hierarchy. This arrangement of shapes provides the optimum combination of superhydrophobicity and surface integrity. This observation explains why the hierarchical structure of many superhydrophobic leaves follows this order. We also investigated the complex hierarchical structure of Salvinia minima. Owing to its remarkable ability to entrap air and pin the contact line, it exhibits superhydrophobicity along with the much-required Cassie state. These properties of Salvinia minima make it an excellent candidate for developing omniphobic surfaces. © 2015 IOP Publishing Ltd.

Mechanical Engineering

Bioinspiration and Biomimetics

The role of bio-inspired hierarchical structures in wetting

The atomic distribution in catalytically active metallic glass alloys, Pd43Cu27Ni10P20 and Pt57.5Cu14.7Ni5.3P22.5, was investigated using three-dimensional atom probe microscopy. Atom probe analysis showed uniform distribution of constituent elements for both the starting amorphous alloys, with no phase separation. Both the crystallized alloys showed eutectic microstructure with a very sharp interface (0.5 nm as determined from atom probe). The atomic distribution in the devitrified state is explained based on the "fragile liquid" behavior for these noble-metal glassy alloys. © 2015 Sanghita Mridha et al.

Journal of Nanomaterials

Atomic distribution in catalytic amorphous metals

Evolution of atomic distribution during devitrification of a zirconium-based bulk metallic glass, Zr41.2Ti13.8Cu12.5Ni10.0Be22.5, was investigated using three-dimensional atom probe microscopy. Atom probe analysis showed uniform distribution of constituent elements for the as-cast alloy, with no phase separation. The metallic glass was annealed at different temperatures to study the crystallization pathways and the length scale, distribution, and morphology of the phases formed. Devitrification was found to proceed via the formation of a metastable icosahedral phase. The devitrification pathway is explained based on "strong-liquid" behavior of this alloy. © 2015 Elsevier B.V. All rights reserved.

Materials Letters

Evolution of atomic distribution during devitrification of bulk metallic glass investigated by atom probe microscopy

Computing and Systems Technology Division 2015 - Core Programming Area at the 2015 AIChE Annual Meeting

Numerical modelling and simulation of semi-batch free radical polymerization reactor operation using analytical solution with ak gel model

The characterization of aerosol acidity has received increased attention in recent years due to its influence on atmospheric visibility, climate change and human health. Distribution of water soluble inorganic (WSI) ions in 12 different size fractions of aerosols was investigated under two different atmospheric conditions (smoke-haze and non-haze periods) in 2012 using the Micro-Orifice Uniform Deposit Impactor (MOUDI) and nano-MOUDI for the first time in Singapore. To estimate the in situ acidity ([H+]Ins) and in situ aerosol pH (pHIS), the Aerosol Inorganic Model version-IV under deliquescent mode of airborne particles was used at prevailing ambient temperature and relative humidity. The study revealed an increase in the levels of airborne particulate matter (PM) mass and concentrations of WSI ions for all size fractions during the smoke-haze period, which was caused by the trans-boundary transport of biomass burning-impacted air masses from Indonesia. A bimodal distribution was observed for concentrations of SO42−, NO3−, Cl−, K+ and Na+, whereas concentrations of NH4+, Ca2+ and Mg2+ showed a single mode distribution. The concentration of WSI ions in PM1.8 during the smoke-haze period increased by 3.8 (for SO42−) to 10.5 (for K+) times more than those observed during the non-haze period. The pHIS were observed to be lower during the smoke-haze period than that during the non-haze period for all size fractions of PM, indicating that atmospheric aerosols were more acidic due to the influence of biomass burning emissions. The particles in the accumulation mode were more acidic than those in the coarse mode. © 2014, Springer Science+Business Media Dordrecht.

Environmental Geochemistry and Health

In situ acidity and pH of size-fractionated aerosols during a recent smoke-haze episode in Southeast Asia

We propose a Bag-of-Words (BoW) based technique for human action recognition in videos containing challenges like illumination changes, background changes and camera shaking. We build the pose descriptors corresponding to the actions, based on the gradient-weighted optical flow (GWOF) measure, to minimize the noise related to camera shaking. The pose descriptors are clustered and stored in a dictionary of poses. We further generate a reduced dictionary, where words are termed as pose duplet. The pose duplets are constructed by a graphical approach, considering the probability of occurrence of two poses sequentially, during an action. Here, poses of the initial dictionary, are considered as the nodes of a weighted directed graph called the duplet graph. Weight of each edge of the duplet graph is calculated based on the probability of the destination node of the edge to appear after the source node of the edge. The concatenation of the source and destination pose vectors is called pose duplet. We rank the pose duplets according to the weight of the edge between them. We form the reduced dictionary with the pose duplets with high edge weights (called dominant pose duplet). We construct the action descriptors for each actions, using the dominant pose duplets and recognize the actions. The efficacy of the proposed approach is tested on standard datasets. © Springer International Publishing Switzerland 2015.