Adaptability in organisms and artifacts: A multi level perspective on adaptive processes

Abstract Adaptability to changing circumstances is a key feature of living creatures. Understanding such adaptive processes is central to developing successful autonomous artifacts. In this paper two perspectives are brought to bear on the issue of adaptability. The first is a short term perspective which looks at adaptability in terms of the interactions between the agent and the environment. The second perspective involves a hierarchical evolutionary model which seeks to identify higher-order forms of adaptability based on the concept of adaptive meta-constructs. Task orientated and agent-centered models of adaptive processes in artifacts are considered from these two perspectives. The former isrepresented by the fitness function approach found in evolutionary learning, and the latter in terms of the concepts of empowerment and homeokinesis found in models derived from the self-organizing systems approach. A meta-construct approach to adaptability based on the identification of higher level meta-metrics is also outlined. 2009 Published by Elsevier B.V.

High density mangrove plantation enhances surface accretion, surface elevation change, and tree survival in coastal areas susceptible to sea-level rise

Survival, growth, above ground biomass accumulation, soil surface elevation dynamics and nitrogen accumulation in accreted sediments were studied in experimental treatments planted with four different densities (6.96, 3.26, 1.93 and 0.95 seedlings m-2) of the mangrove Rhizophora mucronata in Puttalam Lagoon, Sri Lanka. Measurements were taken over a period of 1171 days and were compared with those from unplanted controls. Trees at the lowest density showed significantly reduced survival, whilst measures of individual tree growth did not differ significantly among treatments. Rates of surface sediment accretion (means ± S.E.) were 13.0 (±1.3), 10.5 (±0.9), 8.4 (±0.3), 6.9 (±0.5) and 5.7 (±0.3) mm yr-1 at planting densities of 6.96, 3.26, 1.93, 0.95, and 0 (unplanted control) seedlings m-2, respectively, showing highly significant differences among treatments. Mean (± S.E.) rates of surface elevation change were much lower than rates of accretion at 2.8 (±0.2), 1.6 (±0.1), 1.1 (±0.2), 0.6 (±0.2) and -0.3 (±0.1) mm yr-1 for 6.96, 3.26, 1.93, 0.95, and 0 seedlings m-2, respectively. All planted treatments appeared to accumulate greater nitrogen concentrations in the sediment compared to the unplanted control, and suggests one potential causal mechanism for the facilitatory effects observed; high densities of plants potentially contribute to the accretion of greater amounts of nutrient rich sediment. While this potential process needs further study, this study demonstrated how higher densities of mangroves enhance rates of sediment accretion and surface elevation, processes that may be crucial in mangrove ecosystem adaptation to sea level rise. There was no evidence that increasing plant density evoked a trade-off with growth and survival of the planted trees. Rather facilitatory effects enhanced survival at high densities, suggesting that local land managers may be able to take advantage of plantation densities to help mitigate sea-level rise effects by encouraging positive soil surface elevation increment, and perhaps even greater nutrient retention to promote mangrove growth and ameliorate nearshore eutrophication in tropical island environments.

Confounds in pictorial sets: The role of complexity and familiarity in basic-level picture processing

Complexity is conventionally defined as the level of detail or intricacy contained within a picture. The study of complexity has received relatively little attention-in part, because of the absence of an acceptable metric. Traditionally, normative ratings of complexity have been based on human judgments. However, this study demonstrates that published norms for visual complexity are biased. Familiarity and learning influence the subjective complexity scores for nonsense shapes, with a significant training x familiarity interaction [F(1,52) = 17.53, p <.05]. Several image-processing techniques were explored as alternative measures of picture and image complexity. A perimeter detection measure correlates strongly with human judgments of the complexity of line drawings of real-world objects and nonsense shapes and captures some of the processes important in judgments of subjective complexity, while removing the bias due to familiarity effects.

From bit level systolic arrays to HDTV processor chips

The paper starts presents the work initially carried out by Queen's University and RSRE (now Qinetiq) in the development of advanced architectures and microchips based on systolic array architectures. The paper outlines how this has led to the development of highly complex designs for high definition TV and highlights work both on advanced signal processing architectures and tool flows for advanced systems. © 2006 IEEE.

Does the level of graphical detail of a virtual handball thrower influence a goal-keeper's motor response?

The authors investigated how different levels of detail (LODs) of a virtual throwing action can influence a handball goalkeeper's motor response. Goalkeepers attempted to stop a virtual ball emanating from five different graphical LODs of the same virtual throwing action. The five levels of detail were: a textured reference level (L0), a non-textured level (L1), a wire-frame level (L2), a point-light-display (PLD) representation (L3) and a PLD level with reduced ball size (L4). For each motor response made by the goalkeeper we measured and analyzed the time to respond (TTR), the percentage of successful motor responses, the distance between the ball and the closest limb (when the stopping motion was incorrect) and the kinematics of the motion. Results showed that TTR, percentage of successful motor responses and distance with the closest limb were not significantly different for any of the five different graphical LODs. However the kinematics of the motion revealed that the trajectory of the stopping limb was significantly different when comparing the L1 and L3 levels, and when comparing the L1 and L4 levels. These differences in the control of the goalkeeper's actions suggests that the different level of information available in the PLD representations ( L3 and L4) are causing the goalkeeper to adopt different motor strategies to control the approach of their limb to stop the ball.

Revealing differences in gene network inference algorithms on the network level by ensemble methods

Motivation: The inference of regulatory networks from large-scale expression data holds great promise because of the potentially causal interpretation of these networks. However, due to the difficulty to establish reliable methods based on observational data there is so far only incomplete knowledge about possibilities and limitations of such inference methods in this context.

Results: In this article, we conduct a statistical analysis investigating differences and similarities of four network inference algorithms, ARACNE, CLR, MRNET and RN, with respect to local network-based measures. We employ ensemble methods allowing to assess the inferability down to the level of individual edges. Our analysis reveals the bias of these inference methods with respect to the inference of various network components and, hence, provides guidance in the interpretation of inferred regulatory networks from expression data. Further, as application we predict the total number of regulatory interactions in human B cells and hypothesize about the role of Myc and its targets regarding molecular information processing.