Self-Organization Promotes the Evolution of Cooperation with Cultural Propagation

In this paper three computational models for the study of the evolution of cooperation under cultural propagation are studied: Kin Selection, Direct Reciprocity and Indirect Reciprocity. Two analyzes are reported, one comparing their behavior between them and a second one identifying the impact that different parameters have in the model dynamics. The results of these analyzes illustrate how game transitions may occur depending of some parameters within the models and also explain how agents adapt to these transitions by individually choosing their attachment to a cooperative attitude. These parameters regulate how cooperation can self-organize under different circumstances. The emergence of the evolution of cooperation as a result of the agent's adapting processes is also discussed

Can We Infer Species Interactions from Co-occurrence Patterns? A Reply to Peterson et al. (2020)

No abstract

Variations on a Theme: Forty years of music, memories, and mistakes

How did music play a consistent role through various memories? In this memoir, I look at the sweet, the traumatic and troubling. I use specific songs as connections to lost loved ones. I pin the power of music to the loss of three important people in my life: my sister, father, and mother. Who were their musical touchstones? Did I share them? Did music run through them as it has always run through me? The memoir is sandwiched by a brief extended metaphor that props up the conceit that we are entering a live concert performance. It is billed as a letter to a lost loved one because it is indeed meant to address that lost one, my sister, my guide. In the opening section I\u27ve lost my voice. I eventually reclaim it and vow that I will perhaps meet my sister at some point in the future

Effect of Ionizing Radiation on the Crystalline Morphology of Ultra High Molecular Weight Polyethylene (UHMWPE)

The two main applications of ionizing radiation and Ultra High Molecular Weight Polyethylene (UHMWPE) are in space radiation shielding and articulating orthopedic implants (hips and knees). Samples are exposed to both proton and gamma irradiation. Proton irradiation doses are varied from 0-8.7 kGy. Proton Irradiation showed significant increases in crosslinking on the surface, which interferes with recrystallization of the polymer. Gamma Irradiation is conducted at a high (2.9 kGy/hr) and low (0.25 kGy/hr) dose rate at integral doses of 75 and 150 kGy. Gamma irradiation shows significant crosslinking and recrystallization in the center of the sample where oxygen diffusion is limited

Can Ecological Interactions be Inferred from Spatial Data?

The characterisation and quantication of ecological interactions, and the construction of species distributions and their associated ecological niches, is of fundamental theoretical and practical importance. In this paper we give an overview of a Bayesian inference framework, developed over the last 10 years, which, using spatial data, offers a general formalism within which ecological interactions may be characterised and quantied. Interactions are identied through deviations of the spatial distribution of co-occurrences of spatial variables relative to a benchmark for the non-interacting system, and based on a statistical ensemble of spatial cells. The formalism allows for the integration of both biotic and abiotic factors of arbitrary resolution. We concentrate on the conceptual and mathematical underpinnings of the formalism, showing how, using the Naive Bayes approximation, it can be used to not only compare and contrast the relative contribution from each variable, but also to construct species distributions and niches based on arbitrary variable type. We show how the formalism can be used to quantify confounding and therefore help disentangle the complex causal chains that are present in ecosystems. We also show species distributions and their associated niches can be used to infer standard "micro" ecological interactions, such as predation and parasitism. We present several representative use cases that validate our framework, both in terms of being consistent with present knowledge of a set of known interactions, as well as making and validating predictions about new, previously unknown interactions in the case of zoonoses

Evidence against memorial facilitation and context-dependent memory effects through the chewing of gum

The experiment examined the prediction that chewing gum at learning and/or recall facilitated subsequent word recall. Chewing gum at learning significantly impaired recall, indicating that the chewing of gum has a detrimental impact upon initial word encoding. In addition, a context-dependent memory effect was reported for those participants who both learned and recalled in the absence of gum, however a context dependent effect was not found with chewing gum. The findings contradict previous research

A Study of Neo-Austrian Economics using an Artificial Stock Market

An agent-based artificial financial market (AFM) is used to study market efficiency and learning in the context of the Neo-Austrian economic paradigm. Efficiency is defined in terms of the 'excess' profits associated with different trading strategies, where excess for an active trading strategy is defined relative to a dynamic buy and hold benchmark. We define an Inefficiency matrix that takes into account the difference in excess profits of one trading strategy versus another ('signal') relative to the standard error of those profits ('noise') and use this statistical measure to gauge the degree of market efficiency. A one-parameter family of trading strategies is considered, the value of the parameter measuring the relative 'informational' advantage of one strategy versus another. Efficiency is then investigated in terms of the composition of the market defined in terms of the relative proportions of traders using a particular strategy and the parameter values associated with the strategies. We show that markets are more efficient when informational advantages are small (small signal) and when there are many coexisting signals. Learning is introduced by considering 'copycat' traders that learn the relative values of the different strategies in the market and copy the most successful one. We show how such learning leads to a more informationally efficient market but can also lead to a less efficient market as measured in terms of excess profits. It is also shown how the presence of exogeneous information shocks that change trader expectations increases efficiency and complicates the inference problem of copycats.Neoaustrian economics, Market efficiency, Artificial financial market, Learning, Adaptation