An investigation of carbon nanotubes obtained from the decomposition of methane over reduced Mg1− xM xAl2O4 spinel catalysts

Carbon nanotubes produced by the treatment of Mg1−xMxAl2O4 (M = Fe, Co, or Ni; x = 0.1, 0.2, 0.3, or 0.4) spinels with an H2–CH4 mixture at 1070 °C have been investigated systematically. The grains of the oxide-metal composite particles are uniformly covered by a weblike network of carbon nanotube bundles, several tens of micrometers long, made up of single-wall nanotubes with a diameter close to 4 nm. Only the smallest metal particles (<5 nm) are involved in the formation of the nanotubes. A macroscopic characterization method involving surface area measurements and chemical analysis has been developed in order to compare the different nanotube specimens. An increase in the transition metal content of the catalyst yields more carbon nanotubes (up to a metal content of 10.0 wt% or x = 0.3), but causes a decrease in carbon quality. The best compromise is to use 6.7 wt% of metal (x = 0.2) in the catalyst. Co gives superior results with respect to both the quantity and quality of the nanotubes. In the case of Fe, the quality is notably hampered by the formation of Fe3C particles.

Influence of land use changes in river basins on diversity and distribution of amphibians

Land-use changes influence local biodiversity directly, and also cumulatively, contribute to regional and global changes in natural systems and quality of life. Consequent to these, direct impacts on the natural resources that support the health and integrity of living beings are evident in recent times. The Western Ghats being one of the global biodiversity hotspots, is reeling under a tremendous pressure from human induced changes in terms of developmental projects like hydel or thermal power plants, big dams, mining activities, unplanned agricultural practices,monoculture plantations, illegal timber logging, etc. This has led to the once contiguous forest habitats to be fragmented in patches, which in turn has led to the shrinkage of original habitat for the wildlife, change in the hydrological regime of the catchment, decreased inflow in streams,human-animal conflicts, etc. Under such circumstances, a proper management practice is called for requiring suitable biological indicators to show the impact of these changes, set priority regions and in developing models for conservation planning. Amphibians are regarded as one of the best biological indicators due to their sensitivity to even the slightest changes in the environment and hence they could be used as surrogates in conservation and management practices. They are the predominating vertebrates with a high degree of endemism (78%) in Western Ghats. The present study is an attempt to bring in the impacts of various land-uses on anuran distribution in three river basins. Sampling was carried out for amphibians during all seasons of 2003-2006 in basins of Sharavathi, Aghanashini and Bedthi. There are as many as 46 species in the region, one of which is new to science and nearly 59% of them are endemic to the Western Ghats. They belong to nine families, Dicroglossidae being represented by 14 species,followed by Rhacophoridae (9 species) and Ranidae (5 species). Species richness is high in Sharavathi river basin, with 36 species, followed by Bedthi 33 and Aghanashini 27. The impact of land-use changes, was investigated in the upper catchment of Sharavathi river basin. Species diversity indices, relative abundance values, percentage endemics gave clear indication of differences in each sub-catchment. Karl Pearson’s correlation coefficient (r) was calculated between species richness, endemics, environmental descriptors, land-use classes and fragmentation metrics. Principal component analysis was performed to depict the influence of these variables. Results show that sub-catchments with lesser percentage of forest, low canopy cover, higher amount of agricultural area, low rainfall have low species richness, less endemic species and abundant non-endemic species, whereas endemism, species richness and abundance of endemic species are more in the sub-catchments with high tree density, endemic trees, canopy cover, rainfall and lower amount of agriculture fields. This analysis aided in prioritising regions in the Sharavathi river basin for further conservation measures.

String-like propagation of the 5-coordinated defect state in supercooled water: molecular origin of dynamic and thermodynamic anomalies

We find that at low temperature water, large amplitude (similar to 60 degrees) rotational jumps propagate like a string, with the length of propagation increasing with lowering temperature. The strings are formed by mobile 5-coordinated water molecules which move like a Glarum defect (J. Chem. Phys., 1960, 33, 1371), causing water molecules on the path to change from 4-coordinated to 5-coordinated and again back to 4-coordinated water, and in the process cause the tagged water molecule to jump, by following essentially the Laage-Hynes mechanism (Science, 2006, 311, 832-835). The effects on relaxation of the propagating defect causing large amplitude jumps are manifested most dramatically in the mean square displacement (MSD) and also in the rotational time correlation function of the O-H bond of the molecule that is visited by the defect (transient transition to the 5-coordinated state). The MSD and the decay of rotational time correlation function, both remain quenched in the absence of any visit by the defect, as postulated by Glarum long time ago. We establish a direct connection between these propagating events and the known thermodynamic and dynamic anomalies in supercooled water. These strings are found largely in the regions that surround the relatively rigid domains of 4-coordinated water molecules. The propagating strings give rise to a noticeable dynamical heterogeneity, quantified here by a sharp rise in the peak of the four-point density response function, chi(4)(t). This dynamics heterogeneity is also responsible for the breakdown of the Stokes-Einstein relation.

Hybrid approaches for clustering

Applications in various domains often lead to very large and frequently high-dimensional data. Successful algorithms must avoid the curse of dimensionality but at the same time should be computationally efficient. Finding useful patterns in large datasets has attracted considerable interest recently. The primary goal of the paper is to implement an efficient Hybrid Tree based clustering method based on CF-Tree and KD-Tree, and combine the clustering methods with KNN-Classification. The implementation of the algorithm involves many issues like good accuracy, less space and less time. We will evaluate the time and space efficiency, data input order sensitivity, and clustering quality through several experiments.

An O(mn) Gomory-Hu Tree Construction Algorithm for Unweighted Graphs

We present a fast algorithm for computing a Gomory-Hu tree or cut tree for an unweighted undirected graph G = (V,E). The expected running time of our algorithm is Õ(mc) where |E| = m and c is the maximum u-vedge connectivity, where u,v ∈ V. When the input graph is also simple (i.e., it has no parallel edges), then the u-v edge connectivity for each pair of vertices u and v is at most n-1; so the expected running time of our algorithm for simple unweighted graphs is Õ(mn).All the algorithms currently known for constructing a Gomory-Hu tree [8,9] use n-1 minimum s-t cut (i.e., max flow) subroutines. This in conjunction with the current fastest Õ(n20/9) max flow algorithm due to Karger and Levine [11] yields the current best running time of Õ(n20/9n) for Gomory-Hu tree construction on simpleunweighted graphs with m edges and n vertices. Thus we present the first Õ(mn) algorithm for constructing a Gomory-Hu tree for simple unweighted graphs.We do not use a max flow subroutine here; we present an efficient tree packing algorithm for computing Steiner edge connectivity and use this algorithm as our main subroutine. The advantage in using a tree packing algorithm for constructing a Gomory-Hu tree is that the work done in computing a minimum Steiner cut for a Steiner set S ⊆ V can be reused for computing a minimum Steiner cut for certain Steiner sets S' ⊆ S.

Threshold-like features in the magnetic response of iron-filled multi-walled carbon nanotube and polymer composite

The magnetic properties of iron-filled multi-walled carbon nanotubes dispersed in polystyrene (Fe-MWNT/PS) have been investigated as a function of Fe-MWNT concentration (0.1-15 wt%) from 300 to 10 K. Electron microscopy studies indicate that Fe nanorods (aspect ratio similar to 5) remain trapped at various lengths of MWNT and are thus, prevented from oxidation as well as aggregation. The magnetization versus applied field (M-H loop) data of 0.1 wt% of Fe-MWNTs in PS show an anomalous narrowing at low temperatures which is due to the significant contribution from shape anisotropy of Fe nanorods. The remanence shows a threshold feature at 1 wt%. The enhanced coercivity shows a maximum at 1 wt% due to the dominant dipolar interactions among Fe nanorods. Also the squareness ratio shows a maximum at 1 wt%.

Symmetry in Scalar Field Topology

Study of symmetric or repeating patterns in scalar fields is important in scientific data analysis because it gives deep insights into the properties of the underlying phenomenon. Though geometric symmetry has been well studied within areas like shape processing, identifying symmetry in scalar fields has remained largely unexplored due to the high computational cost of the associated algorithms. We propose a computationally efficient algorithm for detecting symmetric patterns in a scalar field distribution by analysing the topology of level sets of the scalar field. Our algorithm computes the contour tree of a given scalar field and identifies subtrees that are similar. We define a robust similarity measure for comparing subtrees of the contour tree and use it to group similar subtrees together. Regions of the domain corresponding to subtrees that belong to a common group are extracted and reported to be symmetric. Identifying symmetry in scalar fields finds applications in visualization, data exploration, and feature detection. We describe two applications in detail: symmetry-aware transfer function design and symmetry-aware isosurface extraction.

Design space exploration of systolic realization of QR factorization on a runtime reconfigurable platform

In the world of high performance computing huge efforts have been put to accelerate Numerical Linear Algebra (NLA) kernels like QR Decomposition (QRD) with the added advantage of reconfigurability and scalability. While popular custom hardware solution in form of systolic arrays can deliver high performance, they are not scalable, and hence not commercially viable. In this paper, we show how systolic solutions of QRD can be realized efficiently on REDEFINE, a scalable runtime reconfigurable hardware platform. We propose various enhancements to REDEFINE to meet the custom need of accelerating NLA kernels. We further do the design space exploration of the proposed solution for any arbitrary application of size n × n. We determine the right size of the sub-array in accordance with the optimal pipeline depth of the core execution units and the number of such units to be used per sub-array.

Decision tree design and applications in speech processing

The design and operation of the minimum cost classifier, where the total cost is the sum of the measurement cost and the classification cost, is computationally complex. Noting the difficulties associated with this approach, decision tree design directly from a set of labelled samples is proposed in this paper. The feature space is first partitioned to transform the problem to one of discrete features. The resulting problem is solved by a dynamic programming algorithm over an explicitly ordered state space of all outcomes of all feature subsets. The solution procedure is very general and is applicable to any minimum cost pattern classification problem in which each feature has a finite number of outcomes. These techniques are applied to (i) voiced, unvoiced, and silence classification of speech, and (ii) spoken vowel recognition. The resulting decision trees are operationally very efficient and yield attractive classification accuracies.

Environmental remediation by photocatalysis

Photocatalysis refers to the oxidation and reduction reactions on semiconductor surfaces, mediated by the valence band holes and conduction band electrons, which are generated by the absorption of ultraviolet or visible light radiation. Photocatalysis is widely being practiced for the degradation and mineralization of hazardous organic compounds to CO2 and H2O, reduction of toxic metal ions to their non-toxic states, deactivation and destruction of water borne microorganisms, decomposition of air pollutants like volatile organic compounds, NOx, CO and NH3, degradation of waste plastics and green synthesis of industrially important chemicals. This review attempts to showcase the well established mechanism of photocatalysis, the use of photocatalysts for water and air pollution control,visible light responsive modified-TiO2 and non-TiO2 based materials for environmental and energy applications, and the importance of developing reaction kinetics for a comprehensive understanding and design of the processes.