Impacts of a word-picture training on reading in youth with mixed intellectual disabilities. A waiting-list control group comparison

Individuals with intellectual disabilities (ID) often struggle with learning how to read. Reading difficulties seem to be the most common secondary condition of ID. Only one in five children with mild or moderate ID achieves even minimal literacy skills. However, literacy education for children and adolescents with ID has been largely overlooked by researchers and educators. While there is little research on reading of children with ID, many training studies have been conducted with other populations with reading difficulties. The most common approach of acquiring literacy skills consists of sophisticated programs that train phonological skills and auditory perception. Only few studies investigated the influence of implicit learning on literacy skills. Implicit learning processes seem to be largely independent of age and IQ. Children are sensitive to the statistics of their learning environment. By frequent word reading they acquire implicit knowledge about the frequency of single letters and letter patterns in written words. Additionally, semantic connections not only improve the word understanding, but also facilitate storage of words in memory. Advances in communication technology have introduced new possibilities for remediating literacy skills. Computers can provide training material in attractive ways, for example through animations and immediate feedback .These opportunities can scaffold and support attention processes central to learning. Thus, the aim of this intervention study was to develop and implement a computer based word-picture training, which is based on statistical and semantic learning, and to examine the training effects on reading, spelling and attention in children and adolescents (9-16 years) diagnosed with mental retardation (general IQ  74). Fifty children participated in four to five weekly training sessions of 15-20 minutes over 4 weeks, and completed assessments of attention, reading, spelling, short-term memory and fluid intelligence before and after training. After a first assessment (T1), the entire sample was divided in a training group (group A) and a waiting control group (group B). After 4 weeks of training with group A, a second assessment (T2) was administered with both training groups. Afterwards, group B was trained for 4 weeks, before a last assessment (T3) was carried out in both groups. Overall, the results showed that the word-picture training led to substantial gains on word decoding and attention for both training groups. These effects were preserved six weeks later (group A). There was also a clear tendency of improvement in spelling after training for both groups, although the effect did not reach significance. These findings highlight the fact that an implicit statistical learning training in a playful way by motivating computer programs can not only promote reading development, but also attention in children with intellectual disabilities.

Applied Graph Theory in Computer Vision and Pattern Recognition

This book will serve as a foundation for a variety of useful applications of graph theory to computer vision, pattern recognition, and related areas. It covers a representative set of novel graph-theoretic methods for complex computer vision and pattern recognition tasks. The first part of the book presents the application of graph theory to low-level processing of digital images such as a new method for partitioning a given image into a hierarchy of homogeneous areas using graph pyramids, or a study of the relationship between graph theory and digital topology. Part II presents graph-theoretic learning algorithms for high-level computer vision and pattern recognition applications, including a survey of graph based methodologies for pattern recognition and computer vision, a presentation of a series of computationally efficient algorithms for testing graph isomorphism and related graph matching tasks in pattern recognition and a new graph distance measure to be used for solving graph matching problems. Finally, Part III provides detailed descriptions of several applications of graph-based methods to real-world pattern recognition tasks. It includes a critical review of the main graph-based and structural methods for fingerprint classification, a new method to visualize time series of graphs, and potential applications in computer network monitoring and abnormal event detection.

Light-cone Wilson loop in classical lattice gauge theory

The transverse broadening of an energetic jet passing through a non-Abelian plasma is believed to be described by the thermal expectation value of a light-cone Wilson loop. In this exploratory study, we measure the light-cone Wilson loop with classical lattice gauge theory simulations. We observe, as suggested by previous studies, that there are strong interactions already at short transverse distances, which may lead to more efficient jet quenching than in leading-order perturbation theory. We also verify that the asymptotics of the Wilson loop do not change qualitatively when crossing the light cone, which supports arguments in the literature that infrared contributions to jet quenching can be studied with dimensionally reduced simulations in the space-like domain. Finally we speculate on possibilities for full four-dimensional lattice studies of the same observable, perhaps by employing shifted boundary conditions in order to simulate ensembles boosted by an imaginary velocity.

Compactified N = 1 supersymmetric Yang-Mills theory on the lattice: continuity and the disappearance of the deconfinement transition

Fermion boundary conditions play a relevant role in revealing the confinement mechanism of N=1 supersymmetric Yang-Mills theory with one compactified space-time dimension. A deconfinement phase transition occurs for a sufficiently small compactification radius, equivalent to a high temperature in the thermal theory where antiperiodic fermion boundary conditions are applied. Periodic fermion boundary conditions, on the other hand, are related to the Witten index and confinement is expected to persist independently of the length of the compactified dimension. We study this aspect with lattice Monte Carlo simulations for different values of the fermion mass parameter that breaks supersymmetry softly. We find a deconfined region that shrinks when the fermion mass is lowered. Deconfinement takes place between two confined regions at large and small compactification radii, that would correspond to low and high temperatures in the thermal theory. At the smallest fermion masses we find no indication of a deconfinement transition. These results are a first signal for the predicted continuity in the compactification of supersymmetric Yang-Mills theory.

From doubled Chern–Simons–Maxwell lattice gauge theory to extensions of the toric code

We regularize compact and non-compact Abelian Chern–Simons–Maxwell theories on a spatial lattice using the Hamiltonian formulation. We consider a doubled theory with gauge fields living on a lattice and its dual lattice. The Hilbert space of the theory is a product of local Hilbert spaces, each associated with a link and the corresponding dual link. The two electric field operators associated with the link-pair do not commute. In the non-compact case with gauge group R, each local Hilbert space is analogous to the one of a charged “particle” moving in the link-pair group space R2 in a constant “magnetic” background field. In the compact case, the link-pair group space is a torus U(1)2 threaded by k units of quantized “magnetic” flux, with k being the level of the Chern–Simons theory. The holonomies of the torus U(1)2 give rise to two self-adjoint extension parameters, which form two non-dynamical background lattice gauge fields that explicitly break the manifest gauge symmetry from U(1) to Z(k). The local Hilbert space of a link-pair then decomposes into representations of a magnetic translation group. In the pure Chern–Simons limit of a large “photon” mass, this results in a Z(k)-symmetric variant of Kitaev’s toric code, self-adjointly extended by the two non-dynamical background lattice gauge fields. Electric charges on the original lattice and on the dual lattice obey mutually anyonic statistics with the statistics angle . Non-Abelian U(k) Berry gauge fields that arise from the self-adjoint extension parameters may be interesting in the context of quantum information processing.

Proof theory for lattice-ordered groups

Proof-theoretic methods are developed and exploited to establish properties of the variety of lattice-ordered groups. In particular, a hypersequent calculus with a cut rule is used to provide an alternative syntactic proof of the generation of the variety by the lattice-ordered group of automorphisms of the real number chain. Completeness is also established for an analytic (cut-free) hypersequent calculus using cut elimination and it is proved that the equational theory of the variety is co-NP complete.

Kaon and D meson masses with N_f = 2+1+1 twisted mass lattice QCD

We discuss the computation of the kaon and D meson masses in the N_f = 2+1+1 twisted mass lattice QCD setup, where explicit heavy flavor and parity breaking occurs at finite lattice spacing. We present three methods suitable in this context and verify their consistency.