Optimizing genetic algorithm strategies for evolving networks

This paper explores the use of genetic algorithms for the design of networks, where the demands on the network fluctuate in time. For varying network constraints, we find the best network using the standard genetic algorithm operators such as inversion, mutation and crossover. We also examine how the choice of genetic algorithm operators affects the quality of the best network found. Such networks typically contain redundancy in servers, where several servers perform the same task and pleiotropy, where servers perform multiple tasks. We explore this trade-off between pleiotropy versus redundancy on the cost versus reliability as a measure of the quality of the network.Comment: 9 pages, 5 figure

Techniques for noise removal from EEG, EOG and air flow signals in sleep patients

Noise is present in the wide variety of signals obtained from sleep patients. This noise comes from a number of sources, from presence of extraneous signals to adjustments in signal amplification and shot noise in the circuits used for data collection. The noise needs to be removed in order to maximize the information gained about the patient using both manual and automatic analysis of the signals. Here we evaluate a number of new techniques for removal of that noise, and the associated problem of separating the original signal sources.Comment: 9 pages, 3 figure

Fluctuations and noise in cancer development

This paper explores fluctuations and noise in various facets of cancer development. The three areas of particular focus are the stochastic progression of cells to cancer, fluctuations of the tumor size during treatment, and noise in cancer cell signalling. We explore the stochastic dynamics of tumor growth and response to treatment using a Markov model, and fluctutions in tumor size in response to treatment using partial differential equations. We also explore noise within gene networks in cancer cells, and noise in inter-cell signalling.Comment: 11 pages, 6 figure

Exploring tradeoffs in pleiotropy and redundancy using evolutionary computing

Evolutionary computation algorithms are increasingly being used to solve optimization problems as they have many advantages over traditional optimization algorithms. In this paper we use evolutionary computation to study the trade-off between pleiotropy and redundancy in a client-server based network. Pleiotropy is a term used to describe components that perform multiple tasks, while redundancy refers to multiple components performing one same task. Pleiotropy reduces cost but lacks robustness, while redundancy increases network reliability but is more costly, as together, pleiotropy and redundancy build flexibility and robustness into systems. Therefore it is desirable to have a network that contains a balance between pleiotropy and redundancy. We explore how factors such as link failure probability, repair rates, and the size of the network influence the design choices that we explore using genetic algorithms.Comment: 10 pages, 6 figure

Gene network analysis and design

Gene networks are composed of many different interacting genes and gene products (RNAs and proteins). They can be thought of as switching regions in n-dimensional space or as mass-balanced signaling networks. Both approaches allow for describing gene networks with the limited quantitative or even qualitative data available. We show how these approaches can be used in modeling the apoptosis gene network that has a vital role in tumor development. The open question is whether engineering changes to this network could be used as a possible cancer treatment

Nonlinear aspects of the EEG during sleep in children

Electroencephalograph (EEG) analysis enables the neuronal behavior of a section of the brain to be examined. If the behavior is nonlinear then nonlinear tools can be used to glean information on brain behavior, and aid in the diagnosis of sleep abnormalities such as obstructive sleep apnea syndrome (OSAS). In this paper the sleep EEGs of a set of normal and mild OSAS children are evaluated for nonlinear behaviour. We consider how the behaviour of the brain changes with sleep stage and between normal and OSAS children.Comment: 9 pages, 2 figures, 4 table

A novel experimental technique and its application to study the effects of particle density and flow submergence on bed particle saltation

This research was sponsored by EPSRC grant EP/G056404/1 which is greatly appreciated.Peer reviewedPublisher PD

Development and management of systemic lupus erythematosus in an HIV-infected man with hepatitis C and B co-infection following interferon therapy: a case report

<p>Abstract</p> <p>Introduction</p> <p>The association of human immunodeficiency virus and immune dysfunction leading to development of autoimmune markers is well described, but human immunodeficiency virus infection is relatively protective for the development of systemic lupus erythematosus. In contrast, development of systemic lupus erythematosus with hepatitis C and with interferon therapy is well described in a number of case reports. We here describe the first case of systemic lupus erythematosus developing in a man infected with human immunodeficiency virus, hepatitis C and hepatitis B co-infection where the onset seems to have been temporally related to interferon therapy.</p> <p>Case presentation</p> <p>We report the occurrence of systemic lupus erythematosus complicating interferon-α therapy for hepatitis C in a 47-year-old asplenic male with haemophilia co-infected with human immunodeficiency virus and hepatitis B. He presented with a truncal rash, abdominal pains and headache and later developed grade IV lupus nephritis requiring haemodialysis, mycophenolate mofetil and steroid therapy. We were able to successfully withdraw dialysis and mycophenolate while maintaining stable renal function.</p> <p>Conclusion</p> <p>Interferon-α is critical in antiviral immunity against hepatitis C but also acts as a pathogenic mediator for systemic lupus erythematosus, a condition associated with activation of plasmacytoid dendritic cells that are depleted in human immunodeficiency virus infection. The occurrence of auto-antibodies and lupus-like features in the coinfections with hepatitis C require careful assessment. Immunosuppressant therapy for lupus risks exacerbating underlying infections in patients with concurrent human immunodeficiency virus, hepatitis B and C.</p