A Spatial Planning Support System for Managing Bangalore's Urban Sprawl

Urban sprawl is the outgrowth along the periphery of cities and along highways. Although an accurate definition of urban sprawl may be debated, a consensus is that urban sprawl is characterized by an unplanned and uneven pattern of growth, driven by multitude of processes and leading to inefficient resource utilization. Urbanization in India has never been as rapid as it is in recent times. As one of the fastest growing economies in the world, India faces stiff challenges in managing the urban sprawl, while ensuring effective delivery of basic services in urban areas. The urban areas contribute significantly to the national economy (more than 50% of GDP), while facing critical challenges in accessing basic services and necessary infrastructure, both social and economic. The overall rise in the population of the urban poor or the increase in travel times due to congestion along road networks are indicators of the effectiveness of planning and governance in assessing and catering for this demand. Agencies of governance at all levels: local bodies, state government and federal government, are facing the brunt of this rapid urban growth. It is imperative for planning and governance to facilitate, augment and service the requisite infrastructure over time systematically. Provision of infrastructure and assurance of the delivery of basic services cannot happen overnight and hence planning has to facilitate forecasting and service provision with appropriate financial mechanisms.

Regulation of extracellular matrix genes by arecoline in primary gingival fibroblasts requires epithelial factors

Background and Objective: Oral submucous fibrosis, a disease of collagen disorder, has been attributed to arecoline present in the saliva of betel quid chewers. However, the molecular basis of the action of arecoline in the pathogenesis of oral submucous fibrosis is poorly understood. The basic aim of our study was to elucidate the mechanism underlying the action of arecoline on the expression of genes in oral fibroblasts. Material and Methods: Human keratinocytes (HaCaT cells) and primary human gingival fibroblasts were treated with arecoline in combination with various pathway inhibitors, and the expression of transforming growth factor-beta isoform genes and of collagen isoforms was assessed using reverse transcription polymerase chain reaction analysis. Results: We observed the induction of transforming growth factor-beta2 by arecoline in HaCaT cells and this induction was found to be caused by activation of the M-3 muscarinic acid receptor via the induction of calcium and the protein kinase C pathway. Most importantly, we showed that transforming growth factor-beta2 was significantly overexpressed in oral submucous fibrosis tissues (p = 0.008), with a median of 2.13 (n = 21) compared with 0.75 (n = 18) in normal buccal mucosal tissues. Furthermore, arecoline down-regulated the expression of collagens 1A1 and 3A1 in human primary gingival fibroblasts; however these collagens were induced by arecoline in the presence of spent medium of cultured human keratinocytes. Treatment with a transforming growth factor-beta blocker, transforming growth factor-beta1 latency-associated peptide, reversed this up-regulation of collagen, suggesting a role for profibrotic cytokines, such as transforming growth factor-beta, in the induction of collagens. Conclusion: Taken together, our data highlight the importance of arecoline-induced epithelial changes in the pathogenesis of oral submucous fibrosis.

A new mixed-matrix membrane for DMFCs

A new mixed-matrix membrane based on stabilized phosphotungstic acid (PTA) incorporated to chitosan (CS)-hydroxy ethyl cellulose (HEC) for application in direct methanol fuel cells (DMFCs) is reported. Membranes are characterised using Fourier Transform Spectroscopy (FTIR), Thermo-Gravimetric Analysis (TGA), Scanning Electron Microscopy (SEM) and their mechanical properties are evaluated. The PTA content in the CS-HEC blend and its influence on proton conductivity, water/methanol sorption, and methanol cross-over in the DMFC is studied. The DMFC with 3 wt. % stabilized PTA-CS-HEC mixed-matrix membrane delivers peak power-density of 58 mW/cm(2) at a load current-density of 210 mA/cm(2) with a lower methanol cross-over than that observed for a DMFC operating with a Nafion membrane electrolyte.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

Facile preparation and some applications of an affinity matrix with a cleavable connector arm containing a disulfide bond

A versatile affinity matrix in which the ligand of interest is linked to the matrix through a connector arm containing a disulfide bond is described. It can be synthesized from any amino-substituted matrix by successive reaction with 2-imino-thio-lane, 5, 5'-dithiobis(2-nitrobenzoic acid), and a thiol derivative of the ligand of choice. The repertoire of ligands can be significantly increased by the appropriate use of avidin-biotin bridges. After adsorption of the material to be fractionated, elution can be effected by reducing the disulfide bond in the connector arm with dithiothreitol. Examples of the preparation and use of various affinity matrices based on amino-substituted Sepharose 6MB are given. One involves the immobilization of the Fab' fragment of a monoclonal antibody against Aspergillus oryzae β-galactosidase and the specific binding of that enzyme to the resulting immunoaffinity matrix. Another involves the immobilization of N-biotinyl-2-thioethylamine followed by complex formation with avidin. The resulting avidin-substituted matrix was used for the selective adsorption and subsequent recovery of mouse hybridoma cells producing anti-avidin antibodies. By further complexing the avidin-substituted matrix with appropriate biotinylated antigens, it should be possible to fractionate cells producing antibodies against a variety of antigens.

High P-T granulite relicts from the Imjingang belt, South Korea:Tectonic significance

This study presents a detailed description on crustal metamorphic signatures of garnet-clinopyroxene-quartz-rutile-bearing high P-T granulites, Samgot unit, Imajingang belt, northwestern Korean Peninsula that formed during Permo-Triassic regional metamorphism related to the amalgamation of East Asian continental fragments. Lenses and blocks of high P-T granulites and garnet-bearing leucosomes occur within mafic metamorphic rocks (mainly amphibolites). The mafic blocks comprise relicts of granoblastic garnet and clinopyroxene with medium-grained quartz and rutile. These relict mineral assemblages are confined to local micro-domains and constitute remnants of peak metamorphism. Plagioclase and amphibole form only as retrograde phases in medium ton coarse-grained moats that rim grain boundaries between relict peak mineral assemblages. This microstructure represents the reaction between garnet, clinopyroxene, quartz and rutile in the presence of melt to form amphibole, plagioclase and titanite with minor biotite. The leucosome domains consist of euhedral garnets within the quartz-K feldspar-plagioclase (granitic) matrix, probably representing peritectic garnet growth along with melting. The rare earth element (REE) composition of minerals also support the peritectic garnet growth with a positive Eu/Eu* (positive Eu anomaly), while the relict garnet shows a slight negative anomaly typical for high-grade granulites. The peak-metamorphic conditions calculated from thermodynamic modeling and compositional isopleths indicate a temperature around c. 900 degrees C at a pressure around c. 20 kbar. The present P-T path indicates a clear multi-stage decompression history with initial decompression and cooling followed by a stage of decompression during hydration possibly during Late Triassic exhumation. The results from this study together with the presence of eclogites from the Hongsung area suggest that the Imjingang area and the western Gyeonggi massif likely resided at crustal levels deeper than those of the eastern and southern part of the Gyeonggi massif. (C) 2009 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.

Cluster based training for scaling non-linear support vector machines

Support Vector Machines(SVMs) are hyperplane classifiers defined in a kernel induced feature space. The data size dependent training time complexity of SVMs usually prohibits its use in applications involving more than a few thousands of data points. In this paper we propose a novel kernel based incremental data clustering approach and its use for scaling Non-linear Support Vector Machines to handle large data sets. The clustering method introduced can find cluster abstractions of the training data in a kernel induced feature space. These cluster abstractions are then used for selective sampling based training of Support Vector Machines to reduce the training time without compromising the generalization performance. Experiments done with real world datasets show that this approach gives good generalization performance at reasonable computational expense.

Highly stable Ag nanoparticles in agar-agar matrix as inorganic-organic hybrid

A novel synthesis of inorganic-organic hybrid films containing well dispersed and almost uniform size Ag nanoparticles in agar-agar matrix has been reported. The films are found to be highly stable for more than a year. The colloidal particles of Ag can be obtained in large quantities in the form of a film or in the gel form when dispersed in agar-agar or by dissolving in a suitable solvent as solution. Characterization has been done by UV-visible spectroscopy and TEM. The hybrid may be of interest to study third-order non-linear susceptibility.

Hanle-Zeeman redistribution matrix. I. Classical theory expressions in the laboratory frame

Polarized scattering in spectral lines is governed by a 4; 4 matrix that describes how the Stokes vector is scattered and redistributed in frequency and direction. Here we develop the theory for this redistribution matrix in the presence of magnetic fields of arbitrary strength and direction. This general magnetic field case is called the Hanle- Zeeman regime, since it covers both of the partially overlapping weak- and strong- field regimes in which the Hanle and Zeeman effects dominate the scattering polarization. In this general regime, the angle-frequency correlations that describe the so-called partial frequency redistribution (PRD) are intimately coupled to the polarization properties. We develop the theory for the PRD redistribution matrix in this general case and explore its detailed mathematical properties and symmetries for the case of a J = 0 -> 1 -> 0 scattering transition, which can be treated in terms of time-dependent classical oscillator theory. It is shown how the redistribution matrix can be expressed as a linear superposition of coherent and noncoherent parts, each of which contain the magnetic redistribution functions that resemble the well- known Hummer- type functions. We also show how the classical theory can be extended to treat atomic and molecular scattering transitions for any combinations of quantum numbers.

MAC design for heterogeneous application support in OFDM based wireless systems

With the increasing adoption of wireless technology, it is reasonable to expect an increase in file demand for supporting both real-time multimedia and high rate reliable data services. Next generation wireless systems employ Orthogonal Frequency Division Multiplexing (OFDM) physical layer owing, to the high data rate transmissions that are possible without increase in bandwidth. Towards improving file performance of these systems, we look at the design of resource allocation algorithms at medium-access layer, and their impact on higher layers. While TCP-based clastic traffic needs reliable transport, UDP-based real-time applications have stringent delay and rate requirements. The MAC algorithms while catering to the heterogeneous service needs of these higher layers, tradeoff between maximizing the system capacity and providing fairness among users. The novelly of this work is the proposal of various channel-aware resource allocation algorithms at the MAC layer. which call result in significant performance gains in an OFDM based wireless system.

OCR Prediction Using Support Vector Machine Based on Piezocone Data

The determination of the overconsolidation ratio (OCR) of clay deposits is an important task in geotechnical engineering practice. This paper examines the potential of a support vector machine (SVM) for predicting the OCR of clays from piezocone penetration test data. SVM is a statistical learning theory based on a structural risk minimization principle that minimizes both error and weight terms. The five input variables used for the SVM model for prediction of OCR are the corrected cone resistance (qt), vertical total stress (sigmav), hydrostatic pore pressure (u0), pore pressure at the cone tip (u1), and the pore pressure just above the cone base (u2). Sensitivity analysis has been performed to investigate the relative importance of each of the input parameters. From the sensitivity analysis, it is clear that qt=primary in situ data influenced by OCR followed by sigmav, u0, u2, and u1. Comparison between SVM and some of the traditional interpretation methods is also presented. The results of this study have shown that the SVM approach has the potential to be a practical tool for determination of OCR.

Support vector machine applied to settlement of shallow foundations on cohesionless soils

The determination of settlement of shallow foundations on cohesionless soil is an important task in geotechnical engineering. Available methods for the determination of settlement are not reliable. In this study, the support vector machine (SVM), a novel type of learning algorithm based on statistical theory, has been used to predict the settlement of shallow foundations on cohesionless soil. SVM uses a regression technique by introducing an ε – insensitive loss function. A thorough sensitive analysis has been made to ascertain which parameters are having maximum influence on settlement. The study shows that SVM has the potential to be a useful and practical tool for prediction of settlement of shallow foundation on cohesionless soil.

Selective dissemination of XML documents based on genetically learned user model and Support Vector Machines

Extensible Markup Language ( XML) has emerged as a medium for interoperability over the Internet. As the number of documents published in the form of XML is increasing, there is a need for selective dissemination of XML documents based on user interests. In the proposed technique, a combination of Adaptive Genetic Algorithms and multi class Support Vector Machine ( SVM) is used to learn a user model. Based on the feedback from the users, the system automatically adapts to the user's preference and interests. The user model and a similarity metric are used for selective dissemination of a continuous stream of XML documents. Experimental evaluations performed over a wide range of XML documents, indicate that the proposed approach significantly improves the performance of the selective dissemination task, with respect to accuracy and efficiency.

Size-dependent magnetic properties of iron carbide nanoparticles embedded in a carbon matrix

Here we report on the magnetic properties of iron carbide nanoparticles embedded in a carbon matrix. Granular distributions of nanoparticles in an inert matrix, of potential use in various applications, were prepared by pyrolysis of organic precursors using the thermally assisted chemical vapour deposition method. By varying the precursor concentration and preparation temperature, compositions with varying iron concentration and nanoparticle sizes were made. Powder x-ray diffraction, transmission electron microscopy and Mossbauer spectroscopy studies revealed the nanocrystalline iron carbide (Fe3C) presence in the partially graphitized matrix. The dependence of the magnetic properties on the particle size and temperature (10 K < T < 300 K) were studied using superconducting quantum interference device magnetometry. Based on the affect of surrounding carbon spins, the observed magnetic behaviour of the nanoparticle compositions, such as the temperature dependence of magnetization and coercivity, can be explained.

Modified density matrix renormalization group algorithm for the zigzag spin-1/2 chain with frustrated antiferromagnetic exchange: Comparison with field theory at large J(2)/J(1)

A modified density matrix renormalization group (DMRG) algorithm is applied to the zigzag spin-1/2 chain with frustrated antiferromagnetic exchange J(1) and J(2) between first and second neighbors. The modified algorithm yields accurate results up to J(2)/J(1) approximate to 4 for the magnetic gap Delta to the lowest triplet state, the amplitude B of the bond order wave phase, the wavelength lambda of the spiral phase, and the spin correlation length xi. The J(2)/J(1) dependences of Delta, B, lambda, and xi provide multiple comparisons to field theories of the zigzag chain. The twist angle of the spiral phase and the spin structure factor yield additional comparisons between DMRG and field theory. Attention is given to the numerical accuracy required to obtain exponentially small gaps or exponentially long correlations near a quantum phase transition.