Recursive Processing of Nested Structures in Monkeys? Two alternative accounts

Ferrigno et al. [2020] introduced an ingenious task to investigate recursion in human and non-human primates. American adults, Tsimane adults, and 3-5 year-old children successfully performed the task. Macaque monkeys required additional training, but two out of three eventually showed good generalization and scored above many Tsimane and child participants. Moreover, when tested on sequences composed of new bracket signs, the monkeys still showed good performance. The authors thus concluded that recursive nesting is not unique to humans. Here, we dispute the claim by showing that at least two alternative interpretations remain tenable. We first examine this conclusion in light of recent findings from modern artificial recurrent neural networks (RNNs), regarding how these networks encode sequences. We show that although RNNs, like monkeys, succeed on demanding generalization tasks as in Ferrigno et al., the underlying neural mechanisms are not recursive. Moreover, we show that when the networks are tested on sequences with deeper center-embedded structures compared to training, the networks fail to generalize. We then discuss an additional interpretation of the results in light of a simple model of sequence memory.

The grammaticalization of term focus structures in Chadic languages: A case of microvariation

This paper argues that the Chadic languages Bura, South Marghi, Hausa, and Guruntum show different stages of the assumed grammaticalization path from bi-clausal cleft structures to mono-clausal constructions for the expression of term focus. This development is characterized by several syntactic and semantic changes, i.e. the reinterpretation of the cleft copula into a focus marker, the loss of the exhaustive inference typically associated with clefts, as well as the loss of syntactic indicators of embedded structures. Based on a microvariational comparison of the four languages, the paper hypothesizes that clefts are diachronically abandoned in favour of mono-clausal focus structures.

Cross-level Correspondence in Q Theory

This paper examines cross-level interactions in basic systems modeling segmental harmony in Q theory (Shih & Inkelas 2019, S&I; see also Inkelas & Shih 2015, 2017). Q theory is a theory of segmental representations that decomposes segments (Qs) into linear strings of subsegments (qs). The component qs can differ in feature values, resulting in Qs with contour tones. S&I present Q theory as an alternative to autosegmental representations and use Agreement-by-correspondence (ABC; Rose & Walker 2004, Hansson 2010, Bennett 2015) analyses to derive various kinds of harmony and dissimilation patterns, particularly those involving tones. This paper shows that while the Q theory typologies share the characteristic structures of ABC(D) systems (Bennett & DelBusso 2018, DelBusso & Bennett to appear) at both qand Qlevels, these (sets of) properties interact in more complex embedded structures.

Centrifuge Testing of Circular and Rectangular Embedded Structures with Base Excitations

We present data and metadata from a centrifuge testing program that was designed to investigate the seismic responses of buried circular and rectangular culverts. The specimen configurations were based on Caltrans Standard Plans, and the scope of research was to compare the experimental findings with the design method described in the NCHRP Report 611 as well as to formulate preliminary recommendations for Caltrans practice. A relatively flexible pipe and a stiff box-shaped specimen embedded in dense sand were tested in the centrifuge at the Center for Geotechnical Modeling at University of California, Davis and were subjected to a set of broadband and harmonic input motions. Responses were recorded in the soil and in the embedded structures using a dense array of instruments. Measured quantities included specimen accelerations, bending strains, and hoop strains; soil accelerations, shear-wave velocities, settlements, and lateral displacements; and accelerations of the centrifuge's shaking table. This data paper describes the tests and summarizes the generated data, which are archived at DesignSafe.ci.org (DOI: 10.17603/DS2XW9R) and are accessible through an interactive Jupyter notebook.

Shape-driven arrest of coffee stain effect drives the fabrication of carbon-nanotube-graphene-oxide inks for printing embedded structures and temperature sensors

Carbon nanotube (CNT) based binder-free, syringe-printable inks, with graphene oxide being used as dispersants, have been designed and developed based on the unique ellipsoidal-particle-shape-mediated arrest of the coffee-stain effect.