Tailoring correlations of the local density of states in disordered photonic materials

We present experimental evidence for the different mechanisms driving the fluctuations of the local density of states (LDOS) in disordered photonic systems. We establish a clear link between the microscopic structure of the material and the frequency correlation function of LDOS accessed by a near-field hyperspectral imaging technique. We show, in particular, that short- and long-range frequency correlations of LDOS are controlled by different physical processes (multiple or single scattering processes, respectively) that can be---to some extent---manipulated independently. We also demonstrate that the single scattering contribution to LDOS fluctuations is sensitive to subwavelength features of the material and, in particular, to the correlation length of its dielectric function. Our work paves a way towards a complete control of statistical properties of disordered photonic systems, allowing for designing materials with predefined correlations of LDOS.Comment: 5+9 pages, 5+6 figures. Fixed confusion of references between the main text and the supplemental material in version

The Impacts of a Reading-to-Dog Programme on Attending and Reading of Nine Children with Autism Spectrum Disorders

Poor knowledge is available on the effectiveness of reading to dogs in educational settings, particularly in children with Autism Spectrum Disorders (ASD). In this study, we test the hypothesis that reading to a dog improves propensity towards books and motivation to read after the end of the programme, as well as reading and cognitive skills in children with ASD. The study is a prospective, randomized controlled trial, consisting of testing and re-testing after a 10 sessions reading programme with and without the presence of a dog. Nine Children with ASD (6-11 years old) were randomly assigned to a control (CG, reading without a dog, n. 4) or experimental group (EG, reading to a dog, n. 5). Children's attendance at reading sessions was recorded at each session. Parents' perceptions were evaluated at the end of the programme to detect changes in children's attitudes and motivation toward reading. Psychologist-administered validated reading (Cornoldi's MT2 reading test; test of reading comprehension, TORC; metaphonological competence test, MCF) and cognitive tests (Wechsler intelligence scale for children Wisc IV, Vineland) to all children, at baseline and at the end of the reading programme. Compared with CG children, children in the EG group participated more frequently in the reading sessions, and they were reported to be more motivated readers at home after the programme. However, there were no differences on reading and cognitive tests' scores either within each group of children or between groups. Further studies are warranted in order to understand whether and how incorporating dogs into a reading programme is beneficial to Children with ASD at the socio-emotional and cognitive level

3D Printed Materials for High Temperature Applications

Additive Manufacturing technologies are proving to be reliable alternatives to traditional ones. Because of their capability to allow short-run production with very low changeover costs and minimal setup, additive manufacturing technologies represent the best choice in case of low-volume highly customized productions. Furthermore, they represent the only alternative to manufacture lattice components, characterized by a complex meso-structure. To date, the main limitation of additive manufacturing is represented by a limited selection of printable materials. In addition, despite lots of information can be found about the mechanical characterization of the available printable materials, there is not as much information regarding their mechanical and geometrical behavior in high-temperature applications. Especially for thermoplastics, the lack of information limits the possibilities for the selection of adequate material, affecting the effectiveness of the design. In this work, a close inspection of the specific literature has been done, with the aim to gather information on the available printable materials suitable for high-temperature applications

Improvements on a MMI based method for automatic texture mapping of 3D dense models

Maximization of Mutual Information routines proved to be suitable for registration of multimodal images. Here a method is proposed to select, in a set of candidates, the image which has a closer resemblance with a given external one. Such algorithm is intended to serve within a wider scope procedure for the automatic texturing of 3D models, where the initial 2D-3D registration problem is shifted to a 2D-2D registration challenge. In order to improve its performance a number of variations in the way the Mutual Information is computed are introduced and a method to judge its reliability is proposed

Improving on fast and automatic texture mapping of 3D dense models

Not all range devices acquire, along with 3D data, the object's texture. Moreover, not always the desired texture is the visible light image. In such cases, currently, an "a posteriori" texturing of a 3D model is mostly performed in a manual or semi-automated fashion, resulting in a subjective and time consuming operation. Matching homologues points between 2D and 3D data in fact proved to be a more complex operation than image to image, or geometry to geometry registration. The method described in this paper is designed to be fully automated. The software takes as input a generic un-textured 3D model and a nonspecific texture image, which could be different from a visible light photograph, but belong to a set of diagnostic images like X rays, UV light, or IR images. It relies on the creation from the 3D model of several 2D depth maps which retains an exact correspondence with the points of the relief. Each depth map is generated from a different external "view point". The number and location of such viewpoints is determined "a priori", but their final position is to be changed and adjusted on a iterative and automatic base, to assure the possibility of an optimal choice. The selection of the best matching depth map is done by picking the depth map which shows the highest similarity with the texture image, based on a 2D-2D registration procedure performed on all generated depth maps. In order to speed up the procedure, a multi-resolution approach is adopted, where the coarse selection is performed on down-sampled images. Cross correlation and Maximization of Mutual Information (MMI) are here both used as similarity measures, exploiting their different and complementary performances depending on the image size