16 resultados para 390107 Environmental and Natural Resources Law

em Indian Institute of Science - Bangalore - Índia


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A new diazotizing reagent for the spectrophotometric determination of nitrite is described. The method is based on diazotization-coupling reaction between dapsone and phloroglucinol in hydrochloric acid medium. The reactions were conducted at room temperature, the molor absorptivity at 425 nm is 4.28 x 10(4) 1 Mol, (1)cm(-1) and was stable for 50 h. Beer's law was obeyed in the nitrite range of 0.008 - 1.0 mug ml(-1). Tolerance limits were tested for 33 species. The method has been found to be applicable for the determination of nitrite in natural and wastewater.

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Gray water treatment and reuse is an immediate option to counter the upcoming water shortages in various parts of world, especially urban areas. Anaerobic treatment of gray water in houses is an alternative low cost, low energy and low sludge generating option that can meet this challenge. Typical problems of fluctuating VFA, low pH and sludge washout at low loading rates with gray water feedstock was overcome in two chambered anaerobic biofilm reactors using natural fibers as the biofilm support. The long term performance of using natural fiber based biofilms at moderate and low organic loading rates (OLR) have been examined. Biofilms raised on natural fibers (coir, ridge-gourd) were similar to that of synthetic media (PVC, polyethylene) at lower OLR when operated in pulse fed mode without effluent recirculation and achieved 80-90% COD removal at HRT of 2 d showing a small variability during start-up. Confocal microscopy of the biofilms on natural fibers indicated thinner biofilms, dense cell architecture and low extra cellular polymeric substances (EPS) compared to synthetic supports and this is believed to be key factor in high performance at low OLR and low strength gray water. Natural fibers are thus shown to be an effective biofilm support that withstand fluctuating characteristic of domestic gray water. (C) 2013 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

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Given an n x n complex matrix A, let mu(A)(x, y) := 1/n vertical bar{1 <= i <= n, Re lambda(i) <= x, Im lambda(i) <= y}vertical bar be the empirical spectral distribution (ESD) of its eigenvalues lambda(i) is an element of C, i = l, ... , n. We consider the limiting distribution (both in probability and in the almost sure convergence sense) of the normalized ESD mu(1/root n An) of a random matrix A(n) = (a(ij))(1 <= i, j <= n), where the random variables a(ij) - E(a(ij)) are i.i.d. copies of a fixed random variable x with unit variance. We prove a universality principle for such ensembles, namely, that the limit distribution in question is independent of the actual choice of x. In particular, in order to compute this distribution, one can assume that x is real or complex Gaussian. As a related result, we show how laws for this ESD follow from laws for the singular value distribution of 1/root n A(n) - zI for complex z. As a corollary, we establish the circular law conjecture (both almost surely and in probability), which asserts that mu(1/root n An) converges to the uniform measure on the unit disc when the a(ij) have zero mean.

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Clustering techniques are used in regional flood frequency analysis (RFFA) to partition watersheds into natural groups or regions with similar hydrologic responses. The linear Kohonen's self‐organizing feature map (SOFM) has been applied as a clustering technique for RFFA in several recent studies. However, it is seldom possible to interpret clusters from the output of an SOFM, irrespective of its size and dimensionality. In this study, we demonstrate that SOFMs may, however, serve as a useful precursor to clustering algorithms. We present a two‐level. SOFM‐based clustering approach to form regions for FFA. In the first level, the SOFM is used to form a two‐dimensional feature map. In the second level, the output nodes of SOFM are clustered using Fuzzy c‐means algorithm to form regions. The optimal number of regions is based on fuzzy cluster validation measures. Effectiveness of the proposed approach in forming homogeneous regions for FFA is illustrated through application to data from watersheds in Indiana, USA. Results show that the performance of the proposed approach to form regions is better than that based on classical SOFM.

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A supply chain ecosystem consists of the elements of the supply chain and the entities that influence the goods, information and financial flows through the supply chain. These influences come through government regulations, human, financial and natural resources, logistics infrastructure and management, etc., and thus affect the supply chain performance. Similarly, all the ecosystem elements also contribute to the risk. The aim of this paper is to identify both performances-based and risk-based decision criteria, which are important and critical to the supply chain. A two step approach using fuzzy AHP and fuzzy technique for order of preference by similarity to ideal solution has been proposed for multi-criteria decision-making and illustrated using a numerical example. The first step does the selection without considering risks and then in the next step suppliers are ranked according to their risk profiles. Later, the two ranks are consolidated into one. In subsequent section, the method is also extended for multi-tier supplier selection. In short, we are presenting a method for the design of a resilient supply chain, in this paper.

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This paper presents additional distributional records of the Sindh awl-headed snake Lytorhynchus paradoxus from India, along with scale counts, measurements and natural history observations of this poorly known species.

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One hundred complexes have been investigated exhibiting D-X center dot center dot center dot A interactions, where X = H, Cl or Li and DX is the `X bond' donor and A is the acceptor. The optimized structures of all these complexes have been used to propose a generalized `Legon-Millen rule' for the angular geometry in all these interactions. A detailed Atoms in Molecules (AIM) theoretical analysis confirms an important conclusion, known in the literature: there is a strong correlation between the electron density at the X center dot center dot center dot A bond critical point (BCP) and the interaction energy for all these interactions. In addition, we show that extrapolation of the fitted line leads to the ionic bond for Li-bonding (electrostatic) while for hydrogen and chlorine bonding, it leads to the covalent bond. Further, we observe a strong correlation between the change in electron density at the D-X BCP and that at the X center dot center dot center dot A BCP, suggesting conservation of the bond order. The correlation found between penetration and electron density at BCP can be very useful for crystal structure analysis, which relies on arbitrary van der Waals radii for estimating penetration. Various criteria proposed for shared-and closed-shell interactions based on electron density topology have been tested for H/Cl/Li bonded complexes. Finally, using the natural bond orbital (NBO) analysis it is shown that the D-X bond weakens upon X bond formation, whether it is ionic (DLi) or covalent (DH/DCl) and the respective indices such as ionicity or covalent bond order decrease. Clearly, one can think of conservation of bond order that includes ionic and covalent contributions to both D-X and X center dot center dot center dot A bonds, for not only X = H/Cl/Li investigated here but also any atom involved in intermolecular bonding.

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This study concerns the relationship between the power law recession coefficient k (in - dQ/dt = kQ(alpha), Q being discharge at the basin outlet) and past average discharge Q(N) (where N is the temporal distance from the center of the selected time span in the past to the recession peak), which serves as a proxy for past storage state of the basin. The strength of the k-Q(N) relationship is characterized by the coefficient of determination R-N(2), which is expected to indicate the basin's ability to hold water for N days. The main objective of this study is to examine how R-N(2) value of a basin is related with its physical characteristics. For this purpose, we use streamflow data from 358 basins in the United States and selected 18 physical parameters for each basin. First, we transform the physical parameters into mutually independent principal components. Then we employ multiple linear regression method to construct a model of R-N(2) in terms of the principal components. Furthermore, we employ step-wise multiple linear regression method to identify the dominant catchment characteristics that influence R-N(2) and their directions of influence. Our results indicate that R-N(2) is appreciably related to catchment characteristics. Particularly, it is noteworthy that the coefficient of determination of the relationship between R-N(2) and the catchment characteristics is 0.643 for N = 45. We found that topographical characteristics of a basin are the most dominant factors in controlling the value of R-N(2). Our results may be suggesting that it is possible to tell about the water holding capacity of a basin by just knowing about a few of its physical characteristics. (C) 2015 Elsevier B.V. All rights reserved.