Ratings of age of acquisition of 299 words across 25 languages: is there a cross-linguistic order of words?

We present a new set of subjective age-of-acquisition (AoA) ratings for 299 words (158 nouns, 141 verbs) in 25 languages from five language families (Afro-Asiatic: Semitic languages; Altaic: one Turkic language: Indo-European: Baltic, Celtic, Germanic, Hellenic, Slavic, and Romance languages; Niger-Congo: one Bantu language; Uralic: Finnic and Ugric languages). Adult native speakers reported the age at which they had learned each word. We present a comparison of the AoA ratings across all languages by contrasting them in pairs. This comparison shows a consistency in the orders of ratings across the 25 languages. The data were then analyzed (1) to ascertain how the demographic characteristics of the participants influenced AoA estimations and (2) to assess differences caused by the exact form of the target question (when did you learn vs. when do children learn this word); (3) to compare the ratings obtained in our study to those of previous studies; and (4) to assess the validity of our study by comparison with quasi-objective AoA norms derived from the MacArthur–Bates Communicative Development Inventories (MB-CDI). All 299 words were judged as being acquired early (mostly before the age of 6 years). AoA ratings were associated with the raters’ social or language status, but not with the raters’ age or education. Parents reported words as being learned earlier, and bilinguals reported learning them later. Estimations of the age at which children learn the words revealed significantly lower ratings of AoA. Finally, comparisons with previous AoA and MB-CDI norms support the validity of the present estimations. Our AoA ratings are available for research or other purposes.

1945 - A new order of centuries? : Hannah Arendt and Hermann Broch’s “The Death of Virgil”

Sociologisk Forsknings digitala arkiv

Compositional Model Repositories via Dynamic Constraint Satisfaction with Order-of-Magnitude Preferences

The predominant knowledge-based approach to automated model construction, compositional modelling, employs a set of models of particular functional components. Its inference mechanism takes a scenario describing the constituent interacting components of a system and translates it into a useful mathematical model. This paper presents a novel compositional modelling approach aimed at building model repositories. It furthers the field in two respects. Firstly, it expands the application domain of compositional modelling to systems that can not be easily described in terms of interacting functional components, such as ecological systems. Secondly, it enables the incorporation of user preferences into the model selection process. These features are achieved by casting the compositional modelling problem as an activity-based dynamic preference constraint satisfaction problem, where the dynamic constraints describe the restrictions imposed over the composition of partial models and the preferences correspond to those of the user of the automated modeller. In addition, the preference levels are represented through the use of symbolic values that differ in orders of magnitude.

The Perception of Smile Attractiveness Variations from Esthetic Norms, Photographic Framing and Order of Presentation

Objectives: To evaluate the attractiveness of a smile according to variations from esthetic norms, photographic framing, and the order of the presentation of photographs.Materials and Methods: A photograph of an individual was selected and digitally manipulated to create the following smiles: an ideal control smile (I), a smile with diastema (D1), a smile with midline deviation (LM3), a smile with deviation from the long axes of the lateral incisors (10D), and a smile with an inverted smile arc (LSRV). The manipulated photographs were developed in framings of the face and of the mouth and evaluated by 20 laypeople. For half the evaluators, the presentation started with facial photographs and, for the other half, the presentation began with the mouth shots. Evaluators were asked to rank the photographs from the least to the most attractive; then, each photograph was awarded a mark (scale of 0.0 to 10.0).Results: In both presentations, the smiles I, LM3, 10D, and LSRV received favorable ratings, whereas the D1 smile got poor ratings. The photographic framings used (face vs mouth) and the order of presentation of the photographs did not influence the rankings.Conclusion: The absence of variations from beauty norms of a smile has a positive impact on its esthetic perception, but variations from the norms do not necessarily result in reduced attractiveness. (Angle Orthod. 2009;79:634-639.)

NUMERICAL DETERMINATION OF THE ORDER OF PHASE-TRANSITIONS IN ISING SYSTEMS WITH MULTISPIN INTERACTIONS

The method of the fourth-order cumulant of Challa, Landau, and Binder is used together with the Monte Carlo histogram technique of Ferrenberg and Swendsen to study the order of the phase transitions of two-dimensional Ising systems with multispin interactions in the horizontal direction and two-body interactions in the vertical direction.

Local order of Pb1-xLaxZr0.40Ti 0.60O3 ferroelectric ceramic materials probed by X-ray absorption and Raman spectroscopies

This paper reports on the structural characterization of Pb 1-xLaxZr0.40Ti0.60O3 (PLZT) ferroelectric ceramic compositions prepared by the conventional solid state reaction method. X-ray absorption spectroscopy (XAS) and Raman spectroscopy were used to probe the local structure of PLZT samples that exhibits a normal and relaxor ferroelectric behavior. From the Zr K-edge and Pb LIII-edge EXAFS spectra, a considerable dissymmetry of Zr and Pb sites was observed in all samples, including those showing a long-range order cubic symmetry and a relaxor behavior. The Raman spectroscopy results confirmed the existence of a local disorder in all PLZT samples through the observation of Raman active vibrational modes. The variation in the intensity of the E(TO 3) mode in the PLZT relaxor samples indicates that the process of correlation between nanodomains stabilizes at temperatures lower than T m. © 2013 Elsevier B.V. All rights reserved.

Differences in larval nutritional requirements and female oviposition preference reflect the order of fruit colonization of Zaprionus indianus and Drosophila simulans

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Word sense disambiguation via high order of learning in complex networks

Complex networks have been employed to model many real systems and as a modeling tool in a myriad of applications. In this paper, we use the framework of complex networks to the problem of supervised classification in the word disambiguation task, which consists in deriving a function from the supervised (or labeled) training data of ambiguous words. Traditional supervised data classification takes into account only topological or physical features of the input data. On the other hand, the human (animal) brain performs both low- and high-level orders of learning and it has facility to identify patterns according to the semantic meaning of the input data. In this paper, we apply a hybrid technique which encompasses both types of learning in the field of word sense disambiguation and show that the high-level order of learning can really improve the accuracy rate of the model. This evidence serves to demonstrate that the internal structures formed by the words do present patterns that, generally, cannot be correctly unveiled by only traditional techniques. Finally, we exhibit the behavior of the model for different weights of the low- and high-level classifiers by plotting decision boundaries. This study helps one to better understand the effectiveness of the model. Copyright (C) EPLA, 2012