Implementing Universal Computation in an Evolutionary System

Evolutionary algorithms are a common tool in engineering and in the study of natural evolution. Here we take their use in a new direction by showing how they can be made to implement a universal computer. We consider populations of individuals with genes whose values are the variables of interest. By allowing them to interact with one another in a specified environment with limited resources, we demonstrate the ability to construct any arbitrary logic circuit. We explore models based on the limits of small and large populations, and show examples of such a system in action, implementing a simple logic circuit.

On the Emergence of Highly Variable Distributions in the Autonomous System Topology

Recent studies have noted that vertex degree in the autonomous system (AS) graph exhibits a highly variable distribution [15, 22]. The most prominent explanatory model for this phenomenon is the Barabási-Albert (B-A) model [5, 2]. A central feature of the B-A model is preferential connectivity—meaning that the likelihood a new node in a growing graph will connect to an existing node is proportional to the existing node’s degree. In this paper we ask whether a more general explanation than the B-A model, and absent the assumption of preferential connectivity, is consistent with empirical data. We are motivated by two observations: first, AS degree and AS size are highly correlated [11]; and second, highly variable AS size can arise simply through exponential growth. We construct a model incorporating exponential growth in the size of the Internet, and in the number of ASes. We then show via analysis that such a model yields a size distribution exhibiting a power-law tail. In such a model, if an AS’s link formation is roughly proportional to its size, then AS degree will also show high variability. We instantiate such a model with empirically derived estimates of growth rates and show that the resulting degree distribution is in good agreement with that of real AS graphs.

To Queue or Not to Queue: When Queueing is Better Than Timesharing in a Distributed System

We examine the question of whether to employ the first-come-first-served (FCFS) discipline or the processor-sharing (PS) discipline at the hosts in a distributed server system. We are interested in the case in which service times are drawn from a heavy-tailed distribution, and so have very high variability. Traditional wisdom when task sizes are highly variable would prefer the PS discipline, because it allows small tasks to avoid being delayed behind large tasks in a queue. However, we show that system performance can actually be significantly better under FCFS queueing, if each task is assigned to a host based on the task's size. By task assignment, we mean an algorithm that inspects incoming tasks and assigns them to hosts for service. The particular task assignment policy we propose is called SITA-E: Size Interval Task Assignment with Equal Load. Surprisingly, under SITA-E, FCFS queueing typically outperforms the PS discipline by a factor of about two, as measured by mean waiting time and mean slowdown (waiting time of task divided by its service time). We compare the FCFS/SITA-E policy to the processor-sharing case analytically; in addition we compare it to a number of other policies in simulation. We show that the benefits of SITA-E are present even in small-scale distributed systems (four or more hosts). Furthermore, SITA-E is a static policy that does not incorporate feedback knowledge of the state of the hosts, which allows for a simple and scalable implementation.

Task Assignment in a Distributed System: Improving Performance by Unbalancing Load

We consider the problem of task assignment in a distributed system (such as a distributed Web server) in which task sizes are drawn from a heavy-tailed distribution. Many task assignment algorithms are based on the heuristic that balancing the load at the server hosts will result in optimal performance. We show this conventional wisdom is less true when the task size distribution is heavy-tailed (as is the case for Web file sizes). We introduce a new task assignment policy, called Size Interval Task Assignment with Variable Load (SITA-V). SITA-V purposely operates the server hosts at different loads, and directs smaller tasks to the lighter-loaded hosts. The result is that SITA-V provably decreases the mean task slowdown by significant factors (up to 1000 or more) where the more heavy-tailed the workload, the greater the improvement factor. We evaluate the tradeoff between improvement in slowdown and increase in waiting time in a system using SITA-V, and show conditions under which SITA-V represents a particularly appealing policy. We conclude with a discussion of the use of SITA-V in a distributed Web server, and show that it is attractive because it has a simple implementation which requires no communication from the server hosts back to the task router.

Expression and function of the neurotrophic factors GDF5 and GDNF in the nigrostriatal system during development and in rat models of Parkinson's disease

Growth/differentiation factor 5 (GDF5) and glial cell line-derived neurotrophic factor (GDNF) are neurotrophic factors that promote the survival of midbrain dopaminergic neurons in vitro and in vivo. Both factors have potent neurotrophic and neuroprotective effects in rat models of Parkinson's disease (PD), and may represent promising new therapies for PD. The aim of the present study was to investigate the endogenous expression and function of GDF5 and GDNF in the nigrostriatal dopaminergic system during development and in rat models of PD. Examination of the temporal expression patterns of endogenous GDF5, GDNF, and their respective receptors, in the developing and adult nigrostriatal dopaminergic system suggest that these factors play important roles in promoting the survival and maturation of midbrain dopaminergic neurons during the period of postnatal programmed cell death. The relative levels of GDF5 and GDNF mRNAs in the midbrain and striatum, and their individual temporal expression patterns during development, suggest that their modes of actions are quite distinct in vivo. Furthermore, the sustained expression of GDF5, GDNF, and their receptors into adulthood suggest roles for these factors in the continued support and maintenance of mature nigrostriatal dopaminergic neurons. The present study found that endogenous GDF5, GDNF, and their receptors are differentially expressed in two 6-hydroxydopamine-induced lesion adult rat models of PD. In both terminal and axonal lesion models of PD, GDF5 mRNA levels in the striatum increased at 10 days post-lesion, while GDNF mRNA levels in the nigrostriatal system decreased at 10 and 28 days post-lesion. Thus, despite the fact that exogenous GDF5 and GDNF have similar effects on midbrain dopaminergic neurons in vitro and in vivo, their endogenous responses to a neurotoxic injury are quite distinct. These results highlight the importance of studying the temporal dynamic changes in neurotrophic factor expression during development and in animal models of PD.

Investigation of the function of the LNX family of E3 ubiquitin ligases in the nervous system

The Lnx1 (Ligand of Numb protein X 1) and Lnx2 genes belong to a family of PDZ domain-containing RING finger domain E3 ubiquitin ligases. mRNA expression for both genes have been reported in early murine central nervous system. However, there have been limited reports with regards to the expression patterns for both the proteins in vivo. Hence, we have attempted to characterize the significance of these proteins in the context of morphology and physiology of the central nervous system. Through our studies, we have attempted to examine closely the expression of these two genes in the murine central nervous system. We have also looked at novel interacting ligands for both proteins. Interacting partners have been examined with particular relevance to possible roles of their interactions with LNX1 and LNX2 in the functioning of the nervous system. Moreover, we have performed loss-of-function studies by way of creation and characterization of knockout mice.

Idiotypic networks and self-recognition in the immune system.

Journal Article

Optimisation methodology for risk mitigation in advanced micro-system electronics manufacturing

This paper presents a design methodology based on numerical modelling, integrated with optimisation techniques and statistical methods, to aid the development of new advanced technologies in the area of micro and nano systems. The design methodology is demonstrated for a micro-machining process called Focused Ion Beam (FIB). This process has been modelled to provide knowledge of how a pre-defined geometry can be achieved through this direct milling. The geometry characterisation is obtained using a Reduced Order Models (ROM), generated from the results of a mathematical model of the Focused Ion Beam, and Design of Experiment (DoE) methods. In this work, the focus is on the design flow methodology which includes an approach on how to include process parameter uncertainties into the process optimisation modelling framework. A discussion on the impact of the process parameters, and their variations, on the quality and performance of the fabricated structure is also presented. The design task is to identify the optimal process conditions, by altering the process parameters, so that certain reliability and confidence of the application is achieved and the imposed constraints are satisfied. The software tools used and developed to demonstrate the design methodology are also presented.

Horizontal and vertical distribution of cirripede cyprid larvae in an upwelling system off the Portuguese coast

The distribution of cirripede cyprids in relation to associated oceanographic conditions was obtained from a grid survey and intensive vertical sampling at a fixed station located 21 km off the northwest Portuguese coast in May 2002. Analysis of cyprid length composition allowed separation of 3 species groups. Chthamalus montagui, Pollicipes pollicipes and Balanus perforatus were largely restricted to the neuston layer and showed only low-amplitude vertical migration. Most C. stellatus cyprids only appeared in the upper 20 m at night, a migration which did not appear to be affected by physical conditions in the water column, but some differences in the vertical migration pattern between days were probably related to varying light penetration. C. montagui is the most abundant adult species found along the Portuguese coast, but C. stellatus cyprids, at densities of up to 8.7 ind. m–3, were the most common sampled in all depth strata at the fixed station. Cyprid horizontal distribution was mainly restricted to an offshore band along the inner shelf, where highest densities were 11 to 15 ind. m–3. This distribution pattern was considered to result from upwelling-favourable wind conditions, creating fronts along the shelf in which the cyprids become concentrated. Cyprid vertical migration, in association with current vertical shear and onshore movement of fronts during upwelling-relaxation periods, may be the mechanisms returning cyprids to the coast to settle. The regularity of these events in the region falls within the period of cyprid viability.

Kinetic Monte Carlo study of electrochemical growth in a heteroepitaxial system

Structural and kinetic aspects of 2-D irreversible metal deposition under potentiostatic conditions are analyzed by means of dynamic Monte Carlo simulations employing embedded atom potentials for a model system. Three limiting models, all considering adatom diffusion, were employed to describe adatom deposition. The first model (A) considers adatom deposition on any free substrate site on the surface at the same rate. The second model (B) considers adatom deposition only on substrate sites which exhibit no neighboring sites occupied by adatoms. The third model (C) allows deposition at higher rates on sites presenting neighboring sites occupied by adatoms. Under the proper conditions, the coverage (theta) versus time (t) relationship for the three cases can be heuristically fitted to the functional form theta = 1 - exp(-betat(alpha)), where alpha and beta are parameters. We suggest that the value of the parameter alpha can be employed to distinguish experimentally between the three cases. While model A trivially delivers a = 1, models B and C are characterized by alpha 1, respectively.