Abstract
Remote-sensing processes based on unmanned aerial vehicles (UAV) have opened up new possibilities to both map and extract individual plant parameters. This is mainly due to the high spatial data resolution and acquisition flexibility of UAVs. Among the possible plant-related metrics is the leaf area index (LAI), which has already been successfully estimated in agronomy and forestry studies using the traditional normalized difference vegetation index from multispectral data or using hyperspectral data. However, the LAI has not been estimated in chestnut trees, and few studies have explored the use of multiple vegetation indices to improve LAI estimation from aerial imagery acquired by UAVs. This study uses multispectral UAV-based data from a chestnut grove to estimate the LAI for each tree by combining vegetation indices computed from different segments of the electromagnetic spectrum with geometrical parameters. Machine-learning techniques were evaluated to predict LAI with robust algorithms that consider dimensionality reduction, avoiding over-fitting, and reduce bias and excess variability. The best achieved coefficient of determination (R-2) value of 85%, which shows that the biophysical and geometrical parameters can explain the LAI variability. This result proves that LAI estimation is improved when using multiple variables instead of a single vegetation index. Furthermore, another significant contribution is a simple, reliable, and precise model that relies on only two variables to estimate the LAI in individual chestnut trees.

Abstract
The evolution of virtual reality (VR) technologies has been notorious, both for leisure activities and for activities related to education. The efficiency of this technology in education leads us to point out several benefits and strengths, for students with specific educational needs (SEN), especially for those with autism spectrum disorders (ASD). In this sense, the growing number of students with ASD requires us to innovate so that we can rehabilitate this group of students, giving them a better quality of life. We can improve their skills: social, behavioural, emotional, cognitive; and even their daily tasks. VR offers a panoply of tools, such as interactive three-dimensional simulations of scenarios that can be used with students with ASD. In this literature review several studies were identified, where they differ in the type of applications developed and the technology used by the students. Although optimism prevails, we need more studies on the use of this technology in educational settings. Thus, this article presents a systematic review of the state of the art on VR perspectives and case studies applied to students with ASD. Case studies are presented where VR technology has been successfully applied and with results that demonstrate the effectiveness of the technology in students with ASD. We are aware that much has to be done still to make the potential of VR an effective reality in the educational context and to allow a better quality of life for students with autism spectrum disorders. Also, we believe that in the next years teachers will be ever more capable of creating specific VR experiences. However, it is essential to have a solid theoretical basis to support the correct use of VR regarding students with ASD. This is our goal with this contribution. © 2022 ACM.

Abstract
Physically-based synthesis of high quality imagery, including global illumination light transport phenomena, results in a significant workload, which makes interactive rendering a very challenging task. We propose a VPL-based ray tracing approach that runs entirely in the GPU and achieves interactive frame rates while handling global illumination light transport phenomena. This approach is based on clustering both shading points and VPLs and computing visibility only among clusters' representatives. A new massively parallel K-means clustering algorithm, enables efficient execution in the GPU. Rendering artifacts, that could result from the piecewise constant approximation of the VPLs/shading points visibility function introduced by the clustering, are smoothed away by resorting to an innovative approach based on fuzzy clustering and weighted interpolation of the visibility function. The effectiveness of the proposed approach is experimentally verified for a collection of scenes, with frame rates larger than 3 fps and up to 25 fps being demonstrated.(c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Abstract
With the continuously growing usage of collaborative robots in industry, the need for achieving a seamless human-robot interaction has also increased, considering that it is a key factor towards reaching a more flexible, effective, and efficient production line. As a prominent and prospective tool to support the human operator to understand and interact with robots, Augmented Reality (AR) has been employed in numerous human-robot collaborative and cooperative industrial applications. Therefore, this systematic literature review critically appraises 32 papers' published between 2016 and 2021 to identify the main employed AR technologies, outline the current state of the art of augmented reality for human-robot collaboration and cooperation, and point out future developments for this research field. Results suggest that this is still an expanding research field, especially with the advent of recent advancements regarding head-mounted displays (HMDs). Moreover, projector-based and HMDs developed approaches are showing promising positive influences over operator-related aspects such as performance, task awareness, and safety feeling, even though HMDs need further maturation in ergonomic aspects. Further research should focus on large-scale assessment of the proposed solutions in industrial environments, involving the solution's target audience, and on establishing standards and guidelines for developing AR assistance systems.

Abstract

Abstract
In the last decade, gamification has been a widely used mechanism to influence behavioral habits in users so that they are more positively involved in learning and business processes. There are many articles or applications that materialize this adoption by showing success stories. However, few are those who mention the dangers of its use. This article shares the main precautions to be taken when creating a gamified strategy, promoting the use of gamification design and evaluation frameworks, in order to create a balanced approach that meets the profiles of its users.