An Algorithmic Approach to the Identification of Rigid Domains in Proteins

Many proteins undergo conformational changes to perform their functions. A simple mechanism of conformational change in proteins is a rigid domain motion, in which two parts of a structure move rigidly with respect to each other. The identification of rigid domains is therefore useful in understanding the structure-function relationship of proteins. Many algorithms, including those in [16], [22], [13], [10], and [19], have been developed to identify rigid domains. In this paper we complement these works by proposing a mathematical definition of a rigid domain. We argue that our definition more accurately captures the intuitive notion of rigid domain in the previous work, than the quantitative definition of a rigid domain introduced by Nichols et al. [19]. Furthermore, our definition admits a practical approximation algorithm. We can prove theoretical guarantee on the quality of the output of our algorithm. We implement a randomized version of our algorithm, and demonstrate its effectiveness on several known protein complexes.     

Kinetics of the Kreis test through response surface methodology

The Kreis test is one of the procedures for early detection of oxidative products of fats and oils. The reaction is complicated, sensitive and continuous. The kinetics of the Kreis test have been studied as a function of reagent, phloroglucinol, oil quantity and incubation period for three oils with different fatty acid profiles, storage life and presence of compounds other than triglycerides. A central composite rotatable design with each factor at five levels required 20 experiments for each oil. The results of experiments carried out in duplicate have been examined by analysis of variance, and polynomials of appropriate degree were fitted to the data. The polyhedron search method was used to compute optimum conditions for carrying out the test for each oil. Three-dimensional graphs were generated to bring out the differences in the oils and the kinetics for each oil. Though “compromised” optimized conditions have been reported, the results indicate the necessity of more detailed investigation into the reaction.     

PSO Based Multi-Objective Approach for Controlling PID Controller

CSTR (Continuous stirred tank reactor) is employed in process control and chemical industries to improve response characteristics and system efficiency. It has a highly nonlinear characteristic that includes complexities in its control and design. Dynamic performance is compassionate to change in system parameters which need more effort for planning a significant controller for CSTR. The reactor temperature changes in either direction from the defined reference value. It is important to note that the intensity of chemical actions inside the CSTR is dependent on the various levels of temperature, and deviation from reference values may cause degradation of biomass quality. Design and implementation of an appropriate adaptive controller for such a nonlinear system are essential. In this paper, a conventional Proportional Integral Derivative (PID) controller is designed. The conventional techniques to deal with constraints suffer severe limitations like it has fixed controller parameters. Hence, A novel method is applied for computing the PID controller parameters using a swarm algorithm that overcomes the conventional controller's limitation. In the proposed technique, PID parameters are tuned by Particle Swarm Optimization (PSO). It is not easy to choose the suitable objective function to design a PID controller using PSO to get an optimal response. In this article, a multi-objective function is proposed for PSO based controller design of CSTR.     

Development of a reduced human user input task allocation method for multiple robots

Task allocation mechanisms are employed by multi-robot systems to efficiently distribute tasks between different robots. Currently, many task allocation methods rely on detailed expert knowledge to coordinate robots. However, it may not be feasible to dedicate an expert human user to a multi-robot system. Hence, a non-expert user may have to specify tasks to a team of robots in some situations. This paper presents a novel reduced human user input multi-robot task allocation technique that utilises Fuzzy Inference Systems (FISs). A two-stage primary and secondary task allocation process is employed to select a team of robots comprising manager and worker robots. A multi-robot mapping and exploration task is utilised as a model task to evaluate the task allocation process. Experiments show that primary task allocation is able to successfully identify and select manager robots. Similarly, secondary task allocation successfully identifies and selects worker robots. Both task allocation processes are also robust to parameter variation permitting intuitive selection of parameter values.     

THE APPLICATIONS OF A GENERALIZED EQUATION OF STATE TO THE CORRELATION AND PREDICTION OF PHASE EQUILIBRIA*

Two methods of generalizing an equation of state are demonstrated and their limitations are outlined. One method involves the correlation of the equation of state constants and the second method involves a recently proposed Generalized Corresponding States Principle based on the properties of two (nonspherical) reference fluids. The PVT properties of pure fluids are represented by a new cubic equation of slate with four parameters which are obtained from vapor pressure and saturated liquid density data. It is demonstrated how a limited amount of data on key components may be used to obtain phase equilibria in mixtures.