We currently understand the mental effects of psychedelics to be caused by agonism or partial agonism of 5-HT2A (and possibly 5-HT2C) receptors, and we understand that psychedelic drugs, especially phenylalkylamines, are fairly selective for these two receptors. This manuscript is a reference work on the receptor affinity pharmacology of psychedelic drugs. New data is presented on the affinity of twenty-five psychedelic drugs at fifty-one receptors, transporters, and ion channels, assayed by the National Institute of Mental Health – Psychoactive Drug Screening Program (NIMH-PDSP). In addition, comparable data gathered from the literature on ten additional drugs is also presented (mostly assayed by the NIMH-PDSP). A new method is introduced for normalizing affinity (Ki) data that factors out potency so that the multi-receptor affinity profiles of different drugs can be directly compared and contrasted. The method is then used to compare the thirty-five drugs in graphical and tabular form. It is shown that psychedelic drugs, especially phenylalkylamines, are not as selective as generally believed, interacting with forty-two of forty-nine broadly assayed sites. The thirty-five drugs of the study have very diverse patterns of interaction with different classes of receptors, emphasizing eighteen different receptors. This diversity of receptor interaction may underlie the qualitative diversity of these drugs. It should be possible to use this diverse set of drugs as probes into the roles played by the various receptor systems in the human mind.

This article lists fourteen open problems in artificial life, each of which is a grand challenge requiring a major advance on a fundamental issue for its solution. Each problem is briefly explained, and, where deemed helpful, some promising paths to its solution are indicated.

Evolution provides a creative fount of complex and subtle adaptations that often surprise the scientists who discover them. However, the creativity of evolution is not limited to the natural world: artificial organisms evolving in computational environments have also elicited surprise and wonder from the researchers studying them. The process of evolution is an algorithmic process that transcends the substrate in which it occurs. Indeed, many researchers in the field of digital evolution can provide examples of how their evolving algorithms and organisms have creatively subverted their expectations or intentions, exposed unrecognized bugs in their code, produced unexpectedly adaptations, or engaged in behaviors and outcomes uncannily convergent with ones found in nature. Such stories routinely reveal surprise and creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. Bugs are fixed, experiments are refocused, and one-off surprises are collapsed into a single data point. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This paper is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems.

From a previous study (4) we know that building hornets destrox or abandon cells whose direction thc did not determine and construct new cells aiccording to their own judgment. So far as thickness of cell walls is concerned, thcre is no difTcrence in construction bv juvenile and adult hornets. In fact, hb the timc thev start building, juvenile hornets aIre of the sanme age as adult hornets and continue building in the snime direction lor the r'st of thcir building period.

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