Old chinese and friends: new approaches to historical linguistics of the Sino-Tibetan area

List J-M, Starostin G, Yunfan L. “Old Chinese and Friends”: new approaches to historical linguistics of the Sino-Tibetan area. Journal of Language Relationship. 2019;17(1-2):1-6

Calibration of the difference between actual and hypothetical valuations in a field experiment

We design and implement a field experiment to elicit and calibrate in-sample hypothetical and actual bids given the presence of other goods and intensity of market experience. Using market goods that possess characteristics beyond the norm but yet remain deliverable, bidding behavior was consistent with theory. But we also observe the average calibration factor for hypothetical bids in the auction with other goods to be more severe (0.3) than for the auction without the goods (0.4). The results support the view that the calibration of hypothetical and actual bidding is good- and context-specific.

Free Will: Real or Illusion - A Debate

Debate on free will with Christian List, Gregg Caruso, and Cory Clark. The exchange is focused on Christian List's book Why Free Will Is Real

Strong and Confined Acids Enable a Catalytic Asymmetric Nazarov Cyclization of Simple Divinyl Ketones

We report a catalytic asymmetric Nazarov cyclization of simple, acylic, alkyl-substituted divinyl ketones using our recently disclosed strong and confined imidodiphosphorimidate Brønsted acids. The corresponding monocyclic cyclopentenones are formed in good yields and excellent regio-, diastereo-, and enantioselectivities. Further, the chemical utility of the obtained enantiopure cyclopentenones is demonstrated

Precision Measurements of Supersymmetry at the International Linear Collider

AbstractWhile the 7 and 8 TeV results from the LHC exclude highly constrained SUSY models with a light sparticle spectrum, less constrained models are still viable. Certain such models promise both discovery of coloured sparticles during the 14 TeV run of the LHC, and a rich spectrum of non-coloured states, accessible at the ILC. The LHC might or might not give a hint of the existence of these electro-weak states, but only at the ILC can measurements with sufficient precision be done to elucidate the details of the model. This contribution reports on studies of such models at the ILC based on simulation of the current detector proposals

Correcting a bias in TIGER rates resulting from high amounts of invariant and singleton cognate sets

In a recent issue of the Journal of Language Evolution, Syrja ̈ nen et al. (2021) investigate the suitabilityof computing Cummins and McInerney’s (2011) TIGER rates for estimating the tree-likeness of linguis-tic datasets compiled for phylogenetic reconstruction. The authors test the TIGER rates on a diverse sample of simulated data, which by and large confirms the usefulness of TIGER rates as an analytic tool for investigating linguistic data, but they test them only on one real-world dataset of Uralic languages which turns out to behave quite differently from the simulated data. When testing the TIGER rates on additional datasets, I detected a bias in the computation which leads to an unnatural increase in those cases where a dataset contains many characters with invariant or singleton states. To overcome this problem, I suggest a modified variant of TIGER rates, which is provided in the form of a freely available Python package. Testing the modified TIGER scores on the simulated data of Syrja ̈ nen et al. shows that the corrected TIGER rates still readily distinguish between different degrees of tree-likeness. Testing them on a dataset in which the number of singletons and invariants was artificially increased further shows that the corrected TIGER rates are not influenced by the bias. A final tests on seven linguistic datasets show the usefulness of the corrected TIGER rates on a larger variety of linguistic datasets and illustrate the importance to take specific aspects of linguistic data into account when using biological methods in the domain of language evolution