Gentlemen, stop your engines!

For fifty years, computer chess has pursued an original goal of Artificial Intelligence, to produce a chess-engine to compete at the highest level. The goal has arguably been achieved, but that success has made it harder to answer questions about the relative playing strengths of man and machine. The proposal here is to approach such questions in a counter-intuitive way, handicapping or stopping-down chess engines so that they play less well. The intrinsic lack of man-machine games may be side-stepped by analysing existing games to place computer engines as accurately as possible on the FIDE ELO scale of human play. Move-sequences may also be assessed for likelihood if computer-assisted cheating is suspected.

Signs of l-doubling constants in NF3

Computed infrared band contours are presented for the two degenerate fundamentals of the NF3 molecule, using the l-resonance band contour program described by Cartwright and Mills, with values of the vibration-rotation constants determined from the microwave spectrum by Morino and co-workers. Computed contours are presented for both possible signs of the l-doubling constant, and comparison with the observed band contours leads to the conclusion that q3 = −121.4 MHz and q4 = +51.4 MHz.

Stops making sense: translational trade-offs and stop codon reassignment

Background Efficient gene expression involves a trade-off between (i) premature termination of protein synthesis; and (ii) readthrough, where the ribosome fails to dissociate at the terminal stop. Sense codons that are similar in sequence to stop codons are more susceptible to nonsense mutation, and are also likely to be more susceptible to transcriptional or translational errors causing premature termination. We therefore expect this trade-off to be influenced by the number of stop codons in the genetic code. Although genetic codes are highly constrained, stop codon number appears to be their most volatile feature. Results In the human genome, codons readily mutable to stops are underrepresented in coding sequences. We construct a simple mathematical model based on the relative likelihoods of premature termination and readthrough. When readthrough occurs, the resultant protein has a tail of amino acid residues incorrectly added to the C-terminus. Our results depend strongly on the number of stop codons in the genetic code. When the code has more stop codons, premature termination is relatively more likely, particularly for longer genes. When the code has fewer stop codons, the length of the tail added by readthrough will, on average, be longer, and thus more deleterious. Comparative analysis of taxa with a range of stop codon numbers suggests that genomes whose code includes more stop codons have shorter coding sequences. Conclusions We suggest that the differing trade-offs presented by alternative genetic codes may result in differences in genome structure. More speculatively, multiple stop codons may mitigate readthrough, counteracting the disadvantage of a higher rate of nonsense mutation. This could help explain the puzzling overrepresentation of stop codons in the canonical genetic code and most variants.

When enough is not enough: information overload and metacognitive decisions to stop studying information

People are often exposed to more information than they can actually remember. Despite this frequent form of information overload, little is known about how much information people choose to remember. Using a novel “stop” paradigm, the current research examined whether and how people choose to stop receiving new—possibly overwhelming—information with the intent to maximize memory performance. Participants were presented with a long list of items and were rewarded for the number of correctly remembered words in a following free recall test. Critically, participants in a stop condition were provided with the option to stop the presentation of the remaining words at any time during the list, whereas participants in a control condition were presented with all items. Across five experiments, we found that participants tended to stop the presentation of the items to maximize the number of recalled items, but this decision ironically led to decreased memory performance relative to the control group. This pattern was consistent even after controlling for possible confounding factors (e.g., task demands). The results indicated a general, false belief that we can remember a larger number of items if we restrict the quantity of learning materials. These findings suggest people have an incomplete understanding of how we remember excessive amounts of information.