Multi-model climate change projections for India under representative concentration pathways

Climate projections for the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC) are made using the newly developed representative concentration pathways (RCPs) under the Coupled Model Inter-comparison Project 5 (CMIP5). This article provides multi-model and multi-scenario temperature and precipitation projections for India for the period 1860-2099 based on the new climate data. We find that CMIP5 ensemble mean climate is closer to observed climate than any individual model. The key findings of this study are: (i) under the business-as-usual (between RCP6.0 and RCP8.5) scenario, mean warming in India is likely to be in the range 1.7-2 degrees C by 2030s and 3.3-4.8 degrees C by 2080s relative to pre-industrial times; (ii) all-India precipitation under the business-as-usual scenario is projected to increase from 4% to 5% by 2030s and from 6% to 14% towards the end of the century (2080s) compared to the 1961-1990 baseline; (iii) while precipitation projections are generally less reliable than temperature projections, model agreement in precipitation projections increases from RCP2.6 to RCP8.5, and from short-to long-term projections, indicating that long-term precipitation projections are generally more robust than their short-term counterparts and (iv) there is a consistent positive trend in frequency of extreme precipitation days (e.g. > 40 mm/day) for decades 2060s and beyond. These new climate projections should be used in future assessment of impact of climate change and adaptation planning. There is need to consider not just the mean climate projections, but also the more important extreme projections in impact studies and as well in adaptation planning.

Representative seismic hazard map of Coimbatore, India

The seismic hazard value of any region depends upon three important components such as probable earthquake location, maximum earthquake magnitude and the attenuation equation. This paper presents a representative way of estimating these three important components considering region specific seismotectonic features. Rupture Based Seismic Hazard Analysis (RBSHA) given by Anbazhagan et al. (2011) is used to determine the probable future earthquake locations. This approach is verified on the earthquake data of Bhuj region. The probable earthquake location for this region is identified considering earthquake data till the year 2000. These identified locations match well with the reported locations after 2000. The further Coimbatore City is selected as the study area to develop a representative seismic hazard map using RBSHA approach and to compare with deterministic seismic hazard analysis. Probable future earthquake zones for Coimbatore are located considering the rupture phenomenon as per energy release theory discussed by Anbazhagan et at (2011). Rupture character of the region has been established by estimating the subsurface rupture length of each source and normalized with respect to the length of the source. Average rupture length of the source with respect to its total length is found to be similar for most of the sources in the region, which is called as the rupture character of the region. Maximum magnitudes of probable zones are estimated considering seismic sources close by and regional rupture character established. Representative GMPEs for the study area have been selected by carrying out efficacy test through an average log likelihood value (LLH) as ranking estimator and considering the Isoseismal map. New seismic hazard map of Coimbatore has been developed using the above regional representative parameters of probable earthquake locations, maximum earthquake magnitude and best suitable GMPEs. The new hazard map gives acceleration values at bedrock for maximum possible earthquakes. These results are compared with deterministic seismic hazard map and recently published probabilistic seismic hazard values. (C) 2014 Elsevier B.V. All rights reserved.

Exploring the Consequences of a Representative ``Disallowed'' Conformation of Aib on a 3(10)-Helical Fold

The structural effects of a representative disallowed conformation of Aib on the 3(10)-helical fold of an octapeptidomimetic are explored. The 1D (H-1, C-13) & 2D NMR, FT-IR and CD data reveal that the octapeptide 1, adopts a 3(10)-helical conformation in solution, as it does in its crystal structure. The C-terminal methyl carboxylate (CO2Me) of 1 was modified into an 1,3-oxazine (Oxa) functional group in the peptidomimetic 2. This modification results in the stabilization of the backbone of the C-terminal Aib (Aib*-Oxa) of 2, in a conformation (phi, =180, 0) that is natively disallowed to Aib. Consequent to the presence of this natively disallowed conformation, the 3(10)-helical fold is not disrupted in the body of the peptidomimetic 2. But the structural distortions that do occur in 2 are primarily in residues in the immediate vicinity of the natively disallowed conformation, rather than in the whole peptide body. Non-native electronic effects resulting from modifications in backbone functional groups can be at the origin of stabilizing residues in natively disallowed conformations. (c) 2014 Wiley Periodicals, Inc. Biopolymers (Pept Sci) 104: 21-36, 2015.

Exploring the Consequences of a Representative ``Disallowed'' Conformation of Aib on a 3(10)-Helical Fold

The structural effects of a representative ``disallowed'' conformation of Aib on the 3(10)-helical fold of an octapeptidomimetic are explored. The 1D (H-1, C-13) & 2D NMR, FT-IR and CD data reveal that the octapeptide 1, adopts a 3(10)- helical conformation in solution, as it does in its crystal structure. The C-terminal methyl carboxylate (CO2Me) of 1 was modified into an 1,3-oxazine (Oxa) functional group in the peptidomimetic 2. This modification results in the stabilization of the backbone of the C-terminal Aib (Aib(star)-Oxa) of 2, in a conformation (phi, psi = 180, 0) that is natively disallowed to Aib. Consequent to the presence of this natively disallowed conformation, the 3(10)- helical fold is not disrupted in the body of the peptidomimetic 2. But the structural distortions that do occur in 2 are primarily in residues in the immediate vicinity of the natively disallowed conformation, rather than in the whole peptide body. Non-native electronic effects resulting from modifications in backbone functional groups can be at the origin of stabilizing residues in natively disallowed conformations. (C) 2014 Wiley Periodicals, Inc. Biopolymers

Exploring the Consequences of a Representative ``Disallowed'' Conformation of Aib on a 3(10)-Helical Fold

The structural effects of a representative ``disallowed'' conformation of Aib on the 3(10)-helical fold of an octapeptidomimetic are explored. The 1D (H-1, C-13) & 2D NMR, FT-IR and CD data reveal that the octapeptide 1, adopts a 3(10)- helical conformation in solution, as it does in its crystal structure. The C-terminal methyl carboxylate (CO2Me) of 1 was modified into an 1,3-oxazine (Oxa) functional group in the peptidomimetic 2. This modification results in the stabilization of the backbone of the C-terminal Aib (Aib(star)-Oxa) of 2, in a conformation (phi, psi = 180, 0) that is natively disallowed to Aib. Consequent to the presence of this natively disallowed conformation, the 3(10)- helical fold is not disrupted in the body of the peptidomimetic 2. But the structural distortions that do occur in 2 are primarily in residues in the immediate vicinity of the natively disallowed conformation, rather than in the whole peptide body. Non-native electronic effects resulting from modifications in backbone functional groups can be at the origin of stabilizing residues in natively disallowed conformations. (C) 2014 Wiley Periodicals, Inc. Biopolymers

DETERMINISTIC ALGORITHMS FOR MATCHING AND PACKING PROBLEMS BASED ON REPRESENTATIVE SETS

In this work, we study the well-known r-DIMENSIONAL k-MATCHING ((r, k)-DM), and r-SET k-PACKING ((r, k)-SP) problems. Given a universe U := U-1 ... U-r and an r-uniform family F subset of U-1 x ... x U-r, the (r, k)-DM problem asks if F admits a collection of k mutually disjoint sets. Given a universe U and an r-uniform family F subset of 2(U), the (r, k)-SP problem asks if F admits a collection of k mutually disjoint sets. We employ techniques based on dynamic programming and representative families. This leads to a deterministic algorithm with running time O(2.851((r-1)k) .vertical bar F vertical bar. n log(2)n . logW) for the weighted version of (r, k)-DM, where W is the maximum weight in the input, and a deterministic algorithm with running time O(2.851((r-0.5501)k).vertical bar F vertical bar.n log(2) n . logW) for the weighted version of (r, k)-SP. Thus, we significantly improve the previous best known deterministic running times for (r, k)-DM and (r, k)-SP and the previous best known running times for their weighted versions. We rely on structural properties of (r, k)-DM and (r, k)-SP to develop algorithms that are faster than those that can be obtained by a standard use of representative sets. Incorporating the principles of iterative expansion, we obtain a better algorithm for (3, k)-DM, running in time O(2.004(3k).vertical bar F vertical bar . n log(2)n). We believe that this algorithm demonstrates an interesting application of representative families in conjunction with more traditional techniques. Furthermore, we present kernels of size O(e(r)r(k-1)(r) logW) for the weighted versions of (r, k)-DM and (r, k)-SP, improving the previous best known kernels of size O(r!r(k-1)(r) logW) for these problems.

Evaluation of the Effectiveness of Representative Methods for Determining Young's Modulus and Hardness from Instrumented Indentation Data

The effectiveness of Oliver & Pharr's (O&P's) method, Cheng & Cheng's (C&C's) method, and a new method developed by our group for estimating Young's modulus and hardness based on instrumented indentation was evaluated for the case of yield stress to reduced Young's modulus ratio (sigma(y)/E-r) >= 4.55 x 10(-4) and hardening coefficient (n) <= 0.45. Dimensional theorem and finite element simulations were applied to produce reference results for this purpose. Both O&P's and C&C's methods overestimated the Young's modulus under some conditions, whereas the error can be controlled within +/- 16% if the formulation was modified with appropriate correction functions. Similar modification was not introduced to our method for determining Young's modulus, while the maximum error of results was around +/- 13%. The errors of hardness values obtained from all the three methods could be even larger and were irreducible with any correction scheme. It is therefore suggested that when hardness values of different materials are concerned, relative comparison of the data obtained from a single standard measurement technique would be more practically useful. It is noted that the ranges of error derived from the analysis could be different if different ranges of material parameters sigma(y)/E-r and n are considered.