Kinetic analysis of magnesium aluminate spinel formation: Effect of MgO:Al2O3 ratio and titania dopant

The mechanistic pathway of MgO-Al₂O₃ reaction in solid state to form MgAl₂O₄ spinel was investigated to correlate the kinetic parameters with ratio of reactants (MgO:Al₂O₃) and with the presence of a doping agent, TiO₂. The time-temperature-expansion data of oxide compacts was analyzed using several model free analyses and model based (linear and non-linear) kinetic algorithms. These indicated that spinel formation process can be best described by single step with n-dimensional Avrami equation for every MgO:Al₂O₃ ratio, irrespective of titania dopant. The activation energy (E_a) of the process was proportional to % spinel formed in each system and validated with quantitative XRD analysis. The higher value of Avrami coefficient (n) in 90 wt% Al₂O₃ compositions has been explained with geometric considerations of powder packing. Incorporations of 1% TiO₂ in the MgO: Al₂O₃ oxide compact did not markedly affect the reaction model, frequency factor and Activation energy.     

An inertia-adaptive particle swarm system with particle mobility factor for improved global optimization

Particle Swarm Optimization (PSO) has recently emerged as a nature-inspired algorithm for real parameter optimization. This article describes a method for improving the final accuracy and the convergence speed of PSO by firstly adding a new coefficient (called mobility factor) to the position updating equation and secondly modulating the inertia weight according to the distance between a particle and the globally best position found so far. The two-fold modification tries to balance between the explorative and exploitative tendencies of the swarm with an objective of achieving better search performance. We also mathematically analyze the effect of the modifications on the dynamics of the PSO algorithm. The new algorithm has been shown to be statistically significantly better than the basic PSO and four of its state-of-the-art variants on a twelve-function test-suite in terms of speed, accuracy, and robustness.     

Verification of distributed systems with local�Cglobal predicates

This paper describes a methodology for developing and verifying a class of distributed systems in which the state space may be discrete or continuous. Our focus is on systems where changes are local in that a small number of components change state while the remainder of the system is unchanged. A proof methodology is developed that ensures global properties, such as invariants and convergence, by guaranteeing local properties within subsystems. This methodology is used to prove the correctness of concrete examples. We present a PVS library of theorems and proofs that can be used to reduce the work required to develop and verify programs in this class. A transformation of these libraries to Java is also outlined.     

Pattern synthesis of centre fed linear array using Taylor one parameter distribution and restricted search Particle Swarm Optimization

In this article, a new method of pattern synthesis of centre fed, equal distance linear array having single and multiple synthesis objectives has been proposed and statistically investigated. Single objective of reduced side lobe level (SLL) and first null beamwidth (FNBW) has been considered separately. Consequently, multiple objectives of beamwidth and side lobe level have been investigated. Synthesis of linear array for suitable objectives has been investigated on Taylor one parameter distribution with equal progressive phase. Excitation amplitude of each array element is taken as optimization parameter where distribution has been optimized using Particle Swarm Optimization (PSO) for achieving low SLL. Later the same has been incorporated for obtaining suitable FNBW. In our optimization algorithm conventional PSO has been modified with a restricted search PSO (RSPSO) where search space has been predefined within excitation amplitude range. PSO within the defined range searches for optimum excitation amplitude to achieve the desired objectives. In order to illustrate the effectiveness of the proposed RSPSO, simulation results of three significant instances of linear array have been presented for both even and odd number of element. The design results obtained using RSPSO have improved result than those obtained using other state of the art evolutionary algorithms like differential evolution (DE), invasive weeds optimization (IWO) and Conventional particle Swarm optimization (CPSO) in a statistically significant way.     

Neonatal bladder rupture: an unusual complication of umbilical catheterization

Bladder injury in the neonatal period is an exceedingly rare phenomenon that is usually iatrogenic. Bladder rupture as a complication of umbilical catheterization in a newborn with urinary ascites, respiratory distress and hematuria is presented and discussed.     

Specifying and proving properties of timed I/O automata using Tempo

Timed I/O automata (TIOA) is a mathematical framework for modeling and verification of distributed systems that involve discrete and continuous dynamics. TIOA can be used for example, to model a real-time software component controlling a physical process. The TIOA model is sufficiently general to subsume other models in use for timed systems. The Tempo Toolset, currently under development, is aimed at supporting system development based on TIOA specifications. The Tempo Toolset is an extension of the IOA toolkit, which provides a specification simulator, a code generator, and both model checking and theorem proving support for analyzing specifications. This paper focuses on the modeling of timed systems and their properties with TIOA and on the use of TAME4TIOA, the TAME (Timed Automata Modeling Environment) based theorem proving support provided in Tempo, for proving system properties, including timing properties. Several examples are provided by way of illustration.