Enhanced interest in letters and numbers in autistic children.

BACKGROUND: An intense and precocious interest in written material, together with a discrepancy between decoding and reading comprehension skills are defining criteria for hyperlexia, which is found in up to 20% of autistic individuals. It may represent the extreme end of a broader interest in written material in autism. This study examines the magnitude and nature of the interest in written material in a large population of autistic and non-autistic children. METHODS: All 701 children (391 autistic, 310 non-autistic) under the age of 7 referred to an autism assessment clinic over a span of 4 years were included. Ordinal logistic regressions assessed the association between diagnosis and the level of interest in letters and numbers. A nested sample of parents of 138 autistic, 99 non-autistic clinical, and 76 typically developing (TD) children completed a detailed questionnaire. Cox proportional hazards models analyzed the age of emergence of these interests. Linear regressions evaluated the association between diagnosis and interest level. The frequency of each behaviour showing interest and competence with letters and numbers were compared. RESULTS: In the two studies, 22 to 37% of autistic children had an intense or exclusive interest in letters. The odds of having a greater interest in letters was 2.78 times higher for autistic children than for non-autistic clinical children of the same age, and 3.49 times higher for the interest in numbers, even if 76% of autistic children were minimally or non-verbal. The age of emergence of these interests did not differ between autistic and TD children and did not depend on their level of oral language. Non-autistic children showed more interest in letters within a social context. LIMITATIONS: The study holds limitations inherent to the use of a phone questionnaire with caregivers and missing sociodemographic information. CONCLUSIONS: The emergence of the interest of autistic children toward written language is contemporaneous to the moment in their development where they display a strong deficit in oral language. Together with recent demonstrations of non-social development of oral language in some autistic children, precocious and intense interest in written material suggests that language acquisition in autism may follow an alternative developmental pathway.

Plasmonic Properties of Self-Assembled Gold Nanocrescents: Implications for Chemical Sensing.

A bottom-up approach, the Langmuir-Blodgett technique, is used for the preparation of composite thin films of gold nanoparticles and polymers: poly(styrene-b-2-vinylpyridine), poly-2-vinylpyridine, and polystyrene. The self-assembly of poly(styrene-b-2-vinylpyridine) at the air-water interface leads to the formation of surface micelles, which serve as a template for the organization of gold nanoparticles into ring assemblies. By using poly-2-vinylpyridine in conjunction with low surface pressure, the distance between nanostructures can be increased, allowing for optical characterization of single nanostructures. Once deposited on a solid substrate, the preorganized gold nanoparticles are subjected to further growth by the reduction of additional gold, leading to a variety of nanostructures which can be divided into two categories: nanocrescents and circular arrays of nanoparticles. The optical properties of individual structures are investigated by optical dark-field spectroscopy and numerical calculations. The plasmonic behavior of the nanostructures is elucidated through the correlation of optical properties with structural features and the identification of dominant plasmon modes. Being based on a self-assembly approach, the reported method allows for the formation of interesting plasmonic materials under ambient conditions, at a relatively large scale, and at low cost. These attributes, in addition to the resonances located in the near-infrared region of the spectrum, make nanocrescents candidates for biological and chemical sensing.

Rank-based methods for modeling dependence between loss triangles.

In order to determine the risk capital for their aggregate portfolio, property and casualty insurance companies must fit a multivariate model to the loss triangle data relating to each of their lines of business. As an inadequate choice of dependence structure may have an undesirable effect on reserve estimation, a two-stage inference strategy is proposed in this paper to assist with model selection and validation. Generalized linear models are first fitted to the margins. Standardized residuals from these models are then linked through a copula selected and validated using rank-based methods. The approach is illustrated with data from six lines of business of a large Canadian insurance company for which two hierarchical dependence models are considered, i.e., a fully nested Archimedean copula structure and a copula-based risk aggregation model.