Specific heat at constant volume in the thermodynamic model

A thermodynamic model for multifragmentation which is frequently used appears to give very different values for specific heat at constant volume depending upon whether canonical or grand canonical ensemble is used. The cause for this discrepancy is analysed.Comment: Revtex, 7 pages including 4 figure

Negative specific heat in a thermodynamic model of multifragmentation

We consider a soluble model of multifragmentation which is similar in spirit to many models which have been used to fit intermediate energy heavy ion collision data. In this model $c_v$ is always positive but for finite nuclei $c_p$ can be negative for some temperatures and pressures. Furthermore, negative values of $c_p$ can be obtained in canonical treatment. One does not need to use the microcanonical ensemble. Negative values for $c_p$ can persist for systems as large as 200 paticles but this depends upon parameters used in the model calculation. As expected, negative specific heats are absent in the thermodynamic limit.Comment: Revtex, 13 pages including 6 figure

Model of multifragmentation, Equation of State and phase transition

We consider a soluble model of multifragmentation which is similar in spirit to many models which have been used to fit intermediate energy heavy ion collision data. We draw a p-V diagram for the model and compare with a p-V diagram obtained from a mean-field theory. We investigate the question of chemical instability in the multifragmentation model. Phase transitions in the model are discussed.Comment: Revtex, 9 pages including 6 figures: some change in the text and Fig.

Implementing Public Health Regulations in Developing Countries: Lessons from the OECD Countries

The enforcement of public health standards is a common problem in many developing countries. Public health agencies lack sufficient resources and, too often, enforcement mechanisms rely on slow and erratic judicial systems. These limitations can make traditional public health regulations difficult to implement. In this article, we examine innovative approaches to the implementation of public health regulations that have emerged in recent years within OECD countries. These approaches aim to improve compliance with health standards, while reducing dependence on both the legal system and the administrative resources of public health agencies. This article begins by discussing some traditional forms of public health regulations; these regulations include administrative searches and inspections as well as licensing measures. Within these traditional forms of public health regulation, there are several ways of improving compliance without substantially increasing administrative costs. These measures include public disclosure and several types of sanctions, which may escalate in severity as an actor continues to flout the public health regulation. In addition to such traditional measures, we discuss more creative approaches to reducing dependence on the judiciary and reducing administrative costs. Dependence on the judiciary can be reduced through increased reliance on alternative dispute resolution methods, such as mediation and arbitrations, as well as through the use of a public health Ombudsman. Administrative costs could also potentially be reduced through the creative use of public-private cooperation measures, such as negotiated rulemaking and self-regulating codes of conduct. Developing countries may find some useful lessons in the innovative approaches described; however, these approaches will likely need to be adapted to fit each country’s particular institutional setting

Improved model reduction and tuning of fractional-order PI(λ)D(μ) controllers for analytical rule extraction with genetic programming

This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this record.Genetic algorithm (GA) has been used in this study for a new approach of suboptimal model reduction in the Nyquist plane and optimal time domain tuning of proportional-integral-derivative (PID) and fractional-order (FO) PI(λ)D(μ) controllers. Simulation studies show that the new Nyquist-based model reduction technique outperforms the conventional H(2)-norm-based reduced parameter modeling technique. With the tuned controller parameters and reduced-order model parameter dataset, optimum tuning rules have been developed with a test-bench of higher-order processes via genetic programming (GP). The GP performs a symbolic regression on the reduced process parameters to evolve a tuning rule which provides the best analytical expression to map the data. The tuning rules are developed for a minimum time domain integral performance index described by a weighted sum of error index and controller effort. From the reported Pareto optimal front of the GP-based optimal rule extraction technique, a trade-off can be made between the complexity of the tuning formulae and the control performance. The efficacy of the single-gene and multi-gene GP-based tuning rules has been compared with the original GA-based control performance for the PID and PI(λ)D(μ) controllers, handling four different classes of representative higher-order processes. These rules are very useful for process control engineers, as they inherit the power of the GA-based tuning methodology, but can be easily calculated without the requirement for running the computationally intensive GA every time. Three-dimensional plots of the required variation in PID/fractional-order PID (FOPID) controller parameters with reduced process parameters have been shown as a guideline for the operator. Parametric robustness of the reported GP-based tuning rules has also been shown with credible simulation examples.This work has been supported by the Department of Science and Technology (DST), Government of India, under the PURSE programme