Structural dependence of density in high molecular weight esters

The effect of molecular structure on density has been examined in high molecular weight esters (molecular weight 300-900), having varying degrees of branching. Densities were calculated from an empirical equation, which agrees well with the experimental values (error +/-1.5%), irrespective of branching. Since density is related to molecular packing and hence to the molecular rotation, in n-alkanes, the glass transition temperature (T(g)) and density both increase with molecular weight, and hence T(g) is directly related to the density. The esters exhibit a complex behavior. In linear esters the T(g) decreases with molecular weight which is explained from group contribution and molecular interactions. In the +-branched esters, however, T(g) decreases with molecular weight until the molecular weight reaches 600 and increases sharply thereafter. The Y-branched esters show an intermediate behavior. The dependence of T(g) on molecular weight has been explained from the segmental motion.

Spin-Selective Correlation Experiment for Measurement of Long-Range J Couplings and for Assignment of (R/S) Enantiomers from the Residual Dipolar Couplings and DFT

We report the C-HETSERF experiment for determination of long- and short-range homo- and heteronuclear scalar couplings ((n)J(HH) and (n)J(XH), n >= 1) of organic molecules with a low sensitivity dilute heteronucleus in natural abundance. The method finds significant advantage in measurement of relative signs of long-range heteronuclear total couplings in chiral organic liquid crystal. The advantage of the method is demonstrated for the measurement of residual dipolar couplings (RDCs) in enantiomers oriented in the chiral liquid crystal with a focus to unambiguously assign R/S designation in a 2D spectrum. The alignment tensor calculated from the experimental RDCs and with the computed structures of enantiomers obtained by DFT calculations provides the size of the back-calculated RDCs. Smaller root-mean-square deviations (rmsd) between experimental and calculated RDCs indicate better agreement with the input structure and its correct designation of the stereogenic center.

Redistribution Mechanisms for Assignment of Heterogeneous Objects

There are p heterogeneous objects to be assigned to n competing agents (n > p) each with unit demand. It is required to design a Groves mechanism for this assignment problem satisfying weak budget balance, individual rationality, and minimizing the budget imbalance. This calls for designing an appropriate rebate function. When the objects are identical, this problem has been solved which we refer as WCO mechanism. We measure the performance of such mechanisms by the redistribution index. We first prove an impossibility theorem which rules out linear rebate functions with non-zero redistribution index in heterogeneous object assignment. Motivated by this theorem,we explore two approaches to get around this impossibility. In the first approach, we show that linear rebate functions with non-zero redistribution index are possible when the valuations for the objects have a certain type of relationship and we design a mechanism with linear rebate function that is worst case optimal. In the second approach, we show that rebate functions with non-zero efficiency are possible if linearity is relaxed. We extend the rebate functions of the WCO mechanism to heterogeneous objects assignment and conjecture them to be worst case optimal.

A reinforcement learning approach to automatic generation control

This paper formulates the automatic generation control (AGC) problem as a stochastic multistage decision problem. A strategy for solving this new AGC problem formulation is presented by using a reinforcement learning (RL) approach This method of obtaining an AGC controller does not depend on any knowledge of the system model and more importantly it admits considerable flexibility in defining the control objective. Two specific RL based AGC algorithms are presented. The first algorithm uses the traditional control objective of limiting area control error (ACE) excursions, where as, in the second algorithm, the controller can restore the load-generation balance by only monitoring deviation in tie line flows and system frequency and it does not need to know or estimate the composite ACE signal as is done by all current approaches. The effectiveness and versatility of the approaches has been demonstrated using a two area AGC model. (C) 2002 Elsevier Science B.V. All rights reserved.

Automatic decomposition of unstructured meshes employing genetic algorithms for parallel FEM computations

Parallel execution of computational mechanics codes requires efficient mesh-partitioning techniques. These mesh-partitioning techniques divide the mesh into specified number of submeshes of approximately the same size and at the same time, minimise the interface nodes of the submeshes. This paper describes a new mesh partitioning technique, employing Genetic Algorithms. The proposed algorithm operates on the deduced graph (dual or nodal graph) of the given finite element mesh rather than directly on the mesh itself. The algorithm works by first constructing a coarse graph approximation using an automatic graph coarsening method. The coarse graph is partitioned and the results are interpolated onto the original graph to initialise an optimisation of the graph partition problem. In practice, hierarchy of (usually more than two) graphs are used to obtain the final graph partition. The proposed partitioning algorithm is applied to graphs derived from unstructured finite element meshes describing practical engineering problems and also several example graphs related to finite element meshes given in the literature. The test results indicate that the proposed GA based graph partitioning algorithm generates high quality partitions and are superior to spectral and multilevel graph partitioning algorithms.

Enantiospecific first total synthesis and assignment of absolute configuration of the sesquiterpene (-)-cucumin H

The first total synthesis of the sesquiterpene (-)-cucumin H, a linear triquinane isolated from Macrocystidia cucumis, has been accomplished starting from (R)-limonene employing two different cyclopentannulation methodologies, which in addition to confirming the structure also established the absolute configuration of the natural product.

Viscoelastic phenomenology based structure assignment for closed-loop vibration control of a beam with sensors and actuators

In this paper we incorporate a novel approach to synthesize a class of closed-loop feedback control, based on the variational structure assignment. Properties of a viscoelastic system are used to design an active feedback controller for an undamped structural system with distributed sensor, actuator and controller. Wave dispersion properties of onedimensional beam system have been studied. Efficiency of the chosen viscoelastic model in enhancing damping and stability properties of one-dimensional viscoelastic bar have been analyzed. The variational structure is projected on a solution space of a closed-loop system involving a weakly damped structure with distributed sensor and actuator with controller. These assign the phenomenology based internal strain rate damping parameter of a viscoelastic system to the usual elastic structure but with active control. In the formulation a model of cantilever beam with non-collocated actuator and sensor has been considered. The formulation leads to the matrix identification problem of two dynamic stiffness matrices. The method has been simplified to obtain control system gains for the free vibration control of a cantilever beam system with collocated actuator-sensor, using quadratic optimal control and pole-placement methods.

Automatic Compilation of MATLAB Programs for Synergistic Execution on Heterogeneous Processors

MATLAB is an array language, initially popular for rapid prototyping, but is now being increasingly used to develop production code for numerical and scientific applications. Typical MATLAB programs have abundant data parallelism. These programs also have control flow dominated scalar regions that have an impact on the program's execution time. Today's computer systems have tremendous computing power in the form of traditional CPU cores and throughput oriented accelerators such as graphics processing units(GPUs). Thus, an approach that maps the control flow dominated regions to the CPU and the data parallel regions to the GPU can significantly improve program performance. In this paper, we present the design and implementation of MEGHA, a compiler that automatically compiles MATLAB programs to enable synergistic execution on heterogeneous processors. Our solution is fully automated and does not require programmer input for identifying data parallel regions. We propose a set of compiler optimizations tailored for MATLAB. Our compiler identifies data parallel regions of the program and composes them into kernels. The problem of combining statements into kernels is formulated as a constrained graph clustering problem. Heuristics are presented to map identified kernels to either the CPU or GPU so that kernel execution on the CPU and the GPU happens synergistically and the amount of data transfer needed is minimized. In order to ensure required data movement for dependencies across basic blocks, we propose a data flow analysis and edge splitting strategy. Thus our compiler automatically handles composition of kernels, mapping of kernels to CPU and GPU, scheduling and insertion of required data transfer. The proposed compiler was implemented and experimental evaluation using a set of MATLAB benchmarks shows that our approach achieves a geometric mean speedup of 19.8X for data parallel benchmarks over native execution of MATLAB.