The Danger Theory and Its Application to Artificial Immune Systems

Over the last decade, a new idea challenging the classical self-non-self viewpoint has become popular amongst immunologists. It is called the Danger Theory. In this conceptual paper, we look at this theory from the perspective of Artificial Immune System practitioners. An overview of the Danger Theory is presented with particular emphasis on analogies in the Artificial Immune Systems world. A number of potential application areas are then used to provide a framing for a critical assessment of the concept, and its relevance for Artificial Immune Systems

A study of mineralisation in the Jew limestone, Rookhope borehole.

The nature and distribution of sulphide and non-sulphide epigenetic mineralisation in a section of the Jew Limestone, Rookhope Borehole, are discussed. The pre-mineralisation textural nature and mineralogical and elemental composition of the host rock and the modification of such under the influence of the hydro thermal activity are considered as well as the trace element distribution pattern in the host rock, geothermometric aspects of the mineral assemblage, and the attitude of the mineralisation. Certain aspects of the physical chemistry of the system are discussed and limits imposed on the composition of the depositing fluid at various stages during the mineralising process. Unusual features of the sphalerite and the epigenetic carbonates as revealed by electron microprobe analysis are emphasised. Several of the results of the study are not in agreement with previously-published data on the Jew Limestone in particular and the Northern Pennine mineralisation in general

The Transfer of Evolved Artificial Immune System Behaviours between Small and Large Scale Robotic Platforms

This paper demonstrates that a set of behaviours evolved in simulation on a miniature robot (epuck) can be transferred to a much larger scale platform (a virtual Pioneer P3-DX) that also differs in shape, sensor type, sensor configuration and programming interface. The chosen architecture uses a reinforcement learning-assisted genetic algorithm to evolve the epuck behaviours, which are encoded as a genetic sequence. This sequence is then used by the Pioneers as part of an adaptive, idiotypic artificial immune system (AIS) control architecture. Testing in three different simulated worlds shows that the Pioneer can use these behaviours to navigate and solve object-tracking tasks successfully, as long as its adaptive AIS mechanism is in place.Comment: 12 pages, 3 figures, 2 tables, 9th International Conference on Artificial Evolution (EA 09)

Effects of crystallographic anisotropy on fracture development and acoustic emission in quartz

Transgranular microcracking is fundamental for the initiation and propagation of all fractures in rocks. The geometry of these microcracks is primarily controlled by the interaction of the imposed stress field with the mineral elastic properties. However, the effects of anisotropic elastic properties of minerals on brittle fracture are not well understood. This study examines the effects of elastic anisotropy of quartz on the geometry of brittle fracture and related acoustic emissions (AE) developed during indentation experiments on single crystals at ambient pressure and temperature. A Hertzian cone crack developed during blunt indentation of a single crystal of flawless Brazilian quartz parallel to the c axis shows geometric deviation away from predictions based on the isotropic case, consistent with trigonal symmetry. The visible cone crack penetration depth varies from 3 to 5 mm and apical angle from 53 to 40. Electron backscatter diffraction (EBSD) mapping of the crack tip shows that fracturing initiates along a ~40 μm wide process zone, comprising damage along overlapping en echelon high-index crystallographic planes, shown by discrete bands of reduced electron backscatter pattern (EBSP) quality (band contrast).Coalescence of these surfaces results in a stepped fracture morphology. Monitoring of AE during indentation reveals that the elastic anisotropy of quartz has a significant effect on AE location and focal mechanisms. Ninety-four AE events were recorded during indentation and show an increasing frequency with increasing load. They correspond to the development of subsidiary concentric cracks peripheral to the main cone crack. The strong and complex anisotropy in seismic velocity (~28% Vp, ~43% Vs with trigonal symmetry) resulted in inaccurate and high uncertainty in AE locations using Geiger location routine with an isotropic velocity model. This problem was overcome by using a relative (master event) location algorithm that only requires a priori knowledge of the velocity structure within the source volume. The AE location results correlate reasonably well to the extent of the observed cone crack. Decomposition of AE source mechanisms of the Geiger relocated events shows dominantly end-member behavior between tensile and compressive vector dipole events, with some double-couple-dominated events and no purely tensile or compressive events. The same events located by the master event algorithm yield greater percentage of vector dipole components and no double-couple events, indicating that AE source mechanism solutions can depend on AE location accuracy, and therefore, relocation routine that is utilized. Calculations show that the crystallographic anisotropy of quartz causes apparent deviation of the moment tensors away from double-couple and pure tensile/compressive sources consistent with the observations. Preliminary modeling of calcite anisotropy shows a response distinct from quartz, indicating that the effects of anisotropy on interpreting AE are complex and require detailed further study

Artificial immune systems

The human immune system has numerous properties that make it ripe for exploitation in the computational domain, such as robustness and fault tolerance, and many different algorithms, collectively termed Artificial Immune Systems (AIS), have been inspired by it. Two generations of AIS are currently in use, with the first generation relying on simplified immune models and the second generation utilising interdisciplinary collaboration to develop a deeper understanding of the immune system and hence produce more complex models. Both generations of algorithms have been successfully applied to a variety of problems, including anomaly detection, pattern recognition, optimisation and robotics. In this chapter an overview of AIS is presented, its evolution is discussed, and it is shown that the diversification of the field is linked to the diversity of the immune system itself, leading to a number of algorithms as opposed to one archetypal system. Two case studies are also presented to help provide insight into the mechanisms of AIS; these are the idiotypic network approach and the Dendritic Cell Algorithm