39 research outputs found
An evolutionary approach to sign language emergence:From state to process
Understanding the relationship between gesture, sign, and speech offers a valuable tool for investigating how language emerges from a nonlinguistic state. We propose that the focus on linguistic status is problematic, and a shift to focus on the processes that shape these systems serves to explain the relationship between them and contributes to the central question of how language evolves
A systematic investigation of gesture kinematics in evolving manual languages in the lab
Item does not contain fulltextSilent gestures consist of complex multi-articulatory movements but are now primarily studied through categorical coding of the referential gesture content. The relation of categorical linguistic content with continuous kinematics is therefore poorly understood. Here, we reanalyzed the video data from a gestural evolution experiment (Motamedi, Schouwstra, Smith, Culbertson, & Kirby, 2019), which showed increases in the systematicity of gesture content over time. We applied computer vision techniques to quantify the kinematics of the original data. Our kinematic analyses demonstrated that gestures become more efficient and less complex in their kinematics over generations of learners. We further detect the systematicity of gesture form on the level of thegesture kinematic interrelations, which directly scales with the systematicity obtained on semantic coding of the gestures. Thus, from continuous kinematics alone, we can tap into linguistic aspects that were previously only approachable through categorical coding of meaning. Finally, going beyond issues of systematicity, we show how unique gesture kinematic dialects emerged over generations as isolated chains of participants gradually diverged over iterations from other chains. We, thereby, conclude that gestures can come to embody the linguistic system at the level of interrelationships between communicative tokens, which should calibrate our theories about form and linguistic content.29 p
Effect of Endodontic Irrigants and Medicaments Mixed with Silver Nanoparticles against Biofilm Formation of Enterococcus faecalis
Introduction: The aim of this study was to evaluate the effectiveness of chlorhexidine (CHX), sodium hypochlorite (NaOCl), calcium hydroxide (CH) and double antibiotic paste (DAP) mixed with silver nanoparticles (AgNPs) against Enterococcus faecalis. Methods and materials: Minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), and biofilm formation inhibition (after 72 h) of the experimental substances alone or mixed with AgNPs were measured against E. faecalis using microtiter plate method. Bacterial cultures turbidity was measured using a spectrophotometer. All procedures were performed in triplicates. Results: The MIC values for CHX, NaOCl, CH and DAP were equal to 0.012, 1.25, 1.6 and 0.156 mg/mL, and their MBC’s were 0.025, 2.5, 0 and 0.625 mg/mL. After mixing them with AgNPs, the MIC’s for CHX, NaOCl, CH and DAP were reduced to 0.0032, 0.158, 0.2 and 0.0391 mg/mL, while their MBC’s were reduced to 0.0064, 0.0632, 0.401 and 0.0156 mg/mL. Biofilm formation inhibition occurred in higher dilutions of all irrigants and medicaments as they were mixed with Ag NPs. Conclusions: Adding AgNPs resulted in an increased antimicrobial activity at the tested dilutions for all experimental substances. More investigations in in vivo conditions are required to confirm the results of this study.Keywords: Calcium Hydroxide; Chlorhexidine; Double Antibiotic Paste; Enterococcus Faecalis; Silver Nanoparticles; Sodium Hypochlorit
The emergence of systematic argument distinctions in artificial sign languages
Word order is a key property by which languages indicate the relationship between a predicate and its arguments. However, sign languages use a number of other modality-specific tools in addition to word order such as spatial agreement, which has been likened to verbal agreement in spoken languages, and role shift, where the signer takes on characteristics of propositional agents. In particular, data from emerging sign languages suggest that, though some use of a conventional word order can appear within a few generations, systematic spatial modulation as a grammatical feature takes time to develop. We experimentally examine the emergence of systematic argument marking beyond word order, investigating how artificial gestural systems evolve over generations of participants in the lab. We find that participants converge on different strategies to disambiguate clause arguments, which become more consistent through the use and transmission of gestures; in some cases this leads to conventionalised iconic spatial contrasts, comparable to those found in natural sign languages. We discuss how our results connect with theoretical issues surrounding the analysis of spatial agreement and role shift in established and newly emerging sign languages, and the possible mechanisms behind its evolution
Evolving artificial sign languages in the lab:From improvised gesture to systematic sign
Recent work on emerging sign languages provides evidence for how key properties of linguistic systems are created. Here we use laboratory experiments to investigate the contribution of two specific mechanisms—interaction and transmission—to the emergence of a manual communication system in silent gesturers. We show that the combined effects of these mechanisms, rather than either alone, maintain communicative efficiency, and lead to a gradual increase of regularity and systematic structure. The gestures initially produced by participants are unsystematic and resemble pantomime, but come to develop key language-like properties similar to those documented in newly emerging sign systems
The cultural evolution of complex linguistic constructions in artificial sign languages
Though most documented sign languages make use of space
to denote relationships between predicate arguments, studies
of emerging sign languages suggest that spatial reference does
not emerge fully-formed but takes time to develop. We present
an artificial sign language learning experiment that expands
the cultural evolutionary framework to investigate complex
linguistic constructions. Our results demonstrate the gradual
emergence of consistent devices to distinguish between sentence
arguments, some of which rely on iconic spatial contrasts.
These findings mirror data from emerging sign languages
and point to the cultural mechanisms that facilitate the
evolution of complex linguistic structures