Utility of the International Classification of Functioning, Disability and Health (ICF) for educational psychologists’ work

Despite embracing a bio-psycho-social perspective, the World Health Organization’s International Classification of Functioning, Disability and Health (ICF) assessment framework has had limited application to date with children who have special educational needs (SEN). This study examines its utility for educational psychologists’ work with children who have Autism Spectrum Disorders (ASD). Mothers of 40 children with ASD aged eight to 12 years were interviewed using a structured protocol based on the ICF framework. The Diagnostic Interview for Social and Communication Disorder (DISCO) was completed with a subset of 19 mothers. Internal consistency and inter-rater reliability of the interview assessments were found to be acceptable and there was evidence for concurrent and discriminant validity. Despite some limitations, initial support for the utility of the ICF model suggests its potential value across educational, health and care fields. Further consideration of its relevance to educational psychologists in new areas of multi-agency working is warranted

Linear-Space Approximate Distance Oracles for Planar, Bounded-Genus, and Minor-Free Graphs

A (1 + eps)-approximate distance oracle for a graph is a data structure that supports approximate point-to-point shortest-path-distance queries. The most relevant measures for a distance-oracle construction are: space, query time, and preprocessing time. There are strong distance-oracle constructions known for planar graphs (Thorup, JACM'04) and, subsequently, minor-excluded graphs (Abraham and Gavoille, PODC'06). However, these require Omega(eps^{-1} n lg n) space for n-node graphs. We argue that a very low space requirement is essential. Since modern computer architectures involve hierarchical memory (caches, primary memory, secondary memory), a high memory requirement in effect may greatly increase the actual running time. Moreover, we would like data structures that can be deployed on small mobile devices, such as handhelds, which have relatively small primary memory. In this paper, for planar graphs, bounded-genus graphs, and minor-excluded graphs we give distance-oracle constructions that require only O(n) space. The big O hides only a fixed constant, independent of \epsilon and independent of genus or size of an excluded minor. The preprocessing times for our distance oracle are also faster than those for the previously known constructions. For planar graphs, the preprocessing time is O(n lg^2 n). However, our constructions have slower query times. For planar graphs, the query time is O(eps^{-2} lg^2 n). For our linear-space results, we can in fact ensure, for any delta > 0, that the space required is only 1 + delta times the space required just to represent the graph itself

The Pandemic Penalty: The Gendered Effects of COVID-19 on Scientific Productivity

Academia serves as a valuable case for studying the effects of social forces on workplace productivity, using a concrete measure of output: scholarly papers. Many academics, especially women, have experienced unprecedented challenges to scholarly productivity during the coronavirus disease 2019 (COVID-19) pandemic. The authors analyze the gender composition of more than 450,000 authorships in the arXiv and bioRxiv scholarly preprint repositories from before and during the COVID-19 pandemic. This analysis reveals that the underrepresentation of women scientists in the last authorship position necessary for retention and promotion in the sciences is growing more inequitable. The authors find differences between the arXiv and bioRxiv repositories in how gender affects first, middle, and sole authorship submission rates before and during the pandemic. A review of existing research and theory outlines potential mechanisms underlying this widening gender gap in productivity during COVID-19. The authors aggregate recommendations for institutional change that could ameliorate challenges to women’s productivity during the pandemic and beyond

Dissection with the Fewest Pieces is Hard, Even to Approximate

We prove that it is NP-hard to dissect one simple orthogonal polygon into another using a given number of pieces, as is approximating the fewest pieces to within a factor of 1+1/1080−ε .National Science Foundation (U.S.) (Grant CCF-1217423)National Science Foundation (U.S.) (Grant CCF-1065125)National Science Foundation (U.S.) (Grant CCF-1420692

Range Queries on Uncertain Data

Given a set $P$ of $n$ uncertain points on the real line, each represented by its one-dimensional probability density function, we consider the problem of building data structures on $P$ to answer range queries of the following three types for any query interval $I$: (1) top-$1$ query: find the point in $P$ that lies in $I$ with the highest probability, (2) top-$k$ query: given any integer $k\leq n$ as part of the query, return the $k$ points in $P$ that lie in $I$ with the highest probabilities, and (3) threshold query: given any threshold $\tau$ as part of the query, return all points of $P$ that lie in $I$ with probabilities at least $\tau$. We present data structures for these range queries with linear or nearly linear space and efficient query time.Comment: 26 pages. A preliminary version of this paper appeared in ISAAC 2014. In this full version, we also present solutions to the most general case of the problem (i.e., the histogram bounded case), which were left as open problems in the preliminary versio

A Time-Space Tradeoff for Triangulations of Points in the Plane

In this paper, we consider time-space trade-offs for reporting a triangulation of points in the plane. The goal is to minimize the amount of working space while keeping the total running time small. We present the first multi-pass algorithm on the problem that returns the edges of a triangulation with their adjacency information. This even improves the previously best known random-access algorithm

Spiral model, jamming percolation and glass-jamming transitions

The Spiral Model (SM) corresponds to a new class of kinetically constrained models introduced in joint works with D.S. Fisher [8,9]. They provide the first example of finite dimensional models with an ideal glass-jamming transition. This is due to an underlying jamming percolation transition which has unconventional features: it is discontinuous (i.e. the percolating cluster is compact at the transition) and the typical size of the clusters diverges faster than any power law, leading to a Vogel-Fulcher-like divergence of the relaxation time. Here we present a detailed physical analysis of SM, see [5] for rigorous proofs. We also show that our arguments for SM does not need any modification contrary to recent claims of Jeng and Schwarz [10].Comment: 9 pages, 7 figures, proceedings for StatPhys2

Does central coherence affect the performance of children with autism in dynamic assessments

Central coherence refers to an in-built propensity to form meaningful links over a wide range of stimuli and to generalize over as wide a range of contexts as possible. In children with autism this ability is diminished, and the impact of central coherence deficits in children with autism have previously been observed using static measures of learning, such as reading comprehension test performance. In this study, the relationship between central coherence and more dynamic indicators of learning are investigated. The responses of 52 children with autism (mean age 9:10 years) on a test of central coherence and a dynamic assessment task were analysed. All the children showed significant improvements in dynamic assessment test scores after mediation; however, among those with below average nonverbal intelligence scores, weak central coherence was significantly associated with smaller gains in performance after teaching. Implications for the validity of dynamic assessments for children with autism are discussed