Ecological immunology of mosquito-malaria interactions: Of non-natural versus natural model systems and their inferences

There has been a recent shift in the literature on mosquito/Plasmodium interactions with an increasingly large number of theoretical and experimental studies focusing on their population biology and evolutionary processes. Ecological immunology of mosquito-malaria interactions - the study of the mechanisms and function of mosquito immune responses to Plasmodium in their ecological and evolutionary context - is particularly important for our understanding of malaria transmission and how to control it. Indeed, describing the processes that create and maintain variation in mosquito immune responses and parasite virulence in natural populations may be as important to this endeavor as describing the immune responses themselves. For historical reasons, Ecological Immunology still largely relies on studies based on non-natural model systems. There are many reasons why current research should favour studies conducted closer to the field and more realistic experimental systems whenever possible. As a result, a number of researchers have raised concerns over the use of artificial host-parasite associations to generate inferences about population-level processes. Here I discuss and review several lines of evidence that, I believe, best illustrate and summarize the limitations of inferences generated using non-natural model systems

Meta-heuristic algorithms in car engine design: a literature survey

Meta-heuristic algorithms are often inspired by natural phenomena, including the evolution of species in Darwinian natural selection theory, ant behaviors in biology, flock behaviors of some birds, and annealing in metallurgy. Due to their great potential in solving difficult optimization problems, meta-heuristic algorithms have found their way into automobile engine design. There are different optimization problems arising in different areas of car engine management including calibration, control system, fault diagnosis, and modeling. In this paper we review the state-of-the-art applications of different meta-heuristic algorithms in engine management systems. The review covers a wide range of research, including the application of meta-heuristic algorithms in engine calibration, optimizing engine control systems, engine fault diagnosis, and optimizing different parts of engines and modeling. The meta-heuristic algorithms reviewed in this paper include evolutionary algorithms, evolution strategy, evolutionary programming, genetic programming, differential evolution, estimation of distribution algorithm, ant colony optimization, particle swarm optimization, memetic algorithms, and artificial immune system

'Immune System Approaches to Intrusion Detection - A Review'

Abstract. The use of artificial immune systems in intrusion detection is an appealing concept for two reasons. Firstly, the human immune system provides the human body with a high level of protection from invading pathogens, in a robust, self-organised and distributed manner. Secondly, current techniques used in computer security are not able to cope with the dynamic and increasingly complex nature of computer systems and their security. It is hoped that biologically inspired approaches in this area, including the use of immune-based systems will be able to meet this challenge. Here we collate the algorithms used, the development of the systems and the outcome of their implementation. It provides an introduction and review of the key developments within this field, in addition to making suggestions for future research

Host defence peptides: antimicrobial and immunomodulatory activity and potential applications for tackling antibiotic-resistant infections

The rapidly increasing incidence of multidrug-resistant infections and the alarmingly low rate of discovery of conventional antibiotics create an urgent need for alternative strategies to treat bacterial infections. Host defence peptides are short cationic molecules produced by the immune systems of most multicellular organisms; they are a class of compounds being actively researched. In this review, we provide an overview of the antimicrobial and immunomodulatory activities of natural host defence peptides, and discuss strategies for creating artificial derivatives with improved biological and pharmacological properties, issues of microbial resistance, and challenges associated with their adaptation for clinical use

The Holland broadcast language

The broadcast language is a programming formalism devised by Holland in 1975, which aims at allowing Genetic Algorithms (GAs) to use an adaptable representation. A GA may provide an efficient method for adaption but still depends on the efficiency of the fitness function used. During long-term evolution, this efficiency could be limited by the fixed representation used by the GA to encode the problem. When a fitness function is very complex, it is desirable to adapt the problem representation employed by the fitness function. By adapting the representation, the broadcast language may overcome the deficiencies caused by fixed problem representation in GAs. This report describes an initial detailed specification and implementation of the broadcast language. Our first motivation is the fact that there is currently no published implementation of broadcast systems (broadcast language-based systems) available. Despite Holland presented the broadcast language in his book “Adaptation in Natural and Artificial systems”, he did not support this approach with experimental studies. Our second motivation is the affirmation made by Holland that broadcast systems could model biochemical networks. Indeed Holland also described how the broadcast language could provide a straightforward representation to a variety of biochemical networks (Genetic Regulatory Networks, Neural Networks, Immune system etc). As these biochemical models share many similarities with Cell Signaling Networks (CSNs), broadcast systems may also be considered to model CSNs. One of our goals, within the ESIGNET project, is to develop an evolutionary system to realize and evolve CSNs in Silico. Examining the broadcast language may provide us with valuable insights to the development of such a system. In this paper, we initially review the Holland broadcast language, we then propose a specification and implementation of the language which is later illustrated with an experiment: modeling different chemical reactions