Sound symbolism refers to the non-arbitrary mappings that exist between phonetic properties of speech sounds and their meaning. Despite there being an extensive literature on the topic, the acoustic features and psychological mechanisms that give rise to sound symbolism are not, as yet, altogether clear. The present study was designed to investigate whether different sets of acoustic cues predict size and shape symbolism, respectively. In two experiments, participants judged whether a given consonant-vowel speech sound was large or small, round or angular, using a size or shape scale. Visual size judgments were predicted by vowel formant F1 in combination with F2, and by vowel duration. Visual shape judgments were, however, predicted by formants F2 and F3. Size and shape symbolism were thus not induced by a common mechanism, but rather were distinctly affected by acoustic properties of speech sounds. These findings portray sound symbolism as a process that is not based merely on broad categorical contrasts, such as round/unround and front/back vowels. Rather, individuals seem to base their sound-symbolic judgments on specific sets of acoustic cues, extracted from speech sounds, which vary across judgment dimensions.

Efforts to understand the brain bases of language face the Mapping Problem: At what level do linguistic computations and representations connect to human neurobiology? We review one approach to this problem that relies on rigorously defined computational models to specify the links between linguistic features and neural signals. Such tools can be used to estimate linguistic predictions, model linguistic features, and specify a sequence of processing steps that may be quantitatively fit to neural signals collected while participants use language. Progress has been helped by advances in machine learning, attention to linguistically interpretable models, and openly shared data sets that allow researchers to compare and contrast a variety of models. We describe one such data set in detail in the Supplementary Appendix. Expected final online publication date for the Annual Review of Linguistics, Volume 8 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

An aerobic oxidative aromatization of simple aliphatic alcohols and anilines under the Pd(OAc)/2,4,6-Collidine/Brønsted acid catalytic system has been established, providing a direct approach for the preparation of diverse substituted quinoline derivatives in high yields with wide functional group tolerance. Practically, the protocol can be easily scaled up to gram-scale and was utilized in the concise formal synthesis of a promising herbicide candidate.

A practical and concise protocol for the efficient preparation of pyrrolo[1,2-a]quinoxalines through a cascade of alcohol oxidation/imine formation/intramolecular cyclization/oxidative dehydrogenation has been established. A series of substituted pyrrolo[1,2-a]quinoxaline derivatives were constructed readily in yields of 53-93% from the cheap primary alcohols by using dioxygen as the terminal oxidant. Remarkably, the fact that no extra metals and additives were necessary makes this unprecedented aerobic oxidation process highly step- and atom-economical. The usefulness of this transformation was further demonstrated with the gram-scale synthesis of compound 3aa under standard conditions.

A new approach has been established for Rh(iii)-catalyzed direct aza oxidative cyclization of non-prefunctionalized azobenzenes to provide 2-aryl-2H-benzotriazoles in good yields, in which AgNO3 instead of conventional azide reagents for the first time functions as the nitrogen source for the nitrogenation reaction. Preliminary mechanistic studies suggest that the Rh(iii)-catalyst could account for the nitration reaction, and subsequently cationic silver species might both play a vital role in the fission of the nitrogen-oxygen bonds in nitro groups and promote aza oxidative cyclization.

A new approach was developed for Pd(II)-catalyzed aromatic coupling of oxabenzonorbornadienes with triarylphosphines as both ligands and aryl donors. Diverse functional groups including halo- (F-, Cl-, and Br-), CF3(-), and furyl groups are well tolerated. For unsymmetrical triarylphosphines, the migration ability of aryls is consistent with the electronic property of substituents and maintains the order EDG-Ar > H-Ar > EWD-Ar (EDG means electron-donating group, EWG means electron-withdrawing group). A preliminary mechanistic study was also disclosed.

In this paper, we investigate the non-critical fluctuations of (net) charges and (net) protons in Au+Au collisions at √ s NN = 7.7, 39 and 200 GeV, using iEBE-VISHNU hybrid model with Poisson fluctuations added in the particle event generator between hydrodynamics and UrQMD. Various effects, such as volume fluctuations hadronic evolution and scatterings, resonance decays, as well as realistic centrality cuts and acceptance cuts have been embedded in our model calculations. With properly tuned parameters, iEBE-VISHNU roughly describe the centrality dependent moments and cumulants of (net) charges and (net) protons measured in experiment. Further comparison simulations show that the volume fluctuation is the dominant factor to influence the multiplicity fluctuations, which makes the higher moments of (net) charges largely deviate from the Poison baselines. We also find that the effects from hadronic evolutions and resonance decays are pretty small or even negligible for the multiplicity fluctuations of both (net) charges and (net) protons. PACS numbers: 25.75.Ld, 25.75.Gz, 25.75.Nq

This study examines several different time-series formalizations of sentence-processing effort, as regards their ability to predict the observed fMRI time-course in regions of the brain. These regressors formalize cognitive theories of language processing involving phrase structure parsing, memory burden, lexical meaning, and other factors such as word sequence probabilities. The results suggest that even in the presence of these covariates, a predictor based on minimalist grammars significantly improves a regression model of the BOLD signal in a posterior temporal region, roughly corresponding to Wernicke’s area.