Torsion and its interaction with other internal forces in EN 1993-1-1: a new approach

This is the accepted version of the following article: [Real, E., Bordallo, J. and Real, E. (2016), Torsion and its interaction with other internal forces in EN 1993-1-1 – a new approach. Steel Construction, 9: 240–248. doi:10.1002/stco.201500005], which has been published in final form at http://onlinelibrary.wiley.com/doi/10.1002/stco.201500005/abstractThis paper presents and clarifies the treatments included in EN 1993-1-1, relating to checking the resistance of the steel cross-sections under torsion and its interaction with other internal forces. Specifically, the origin of the formulations for shear-torsion interaction, which was not found in the literature, is presented. Furthermore, a very simple formulation based on the expressions used for shear-torsion interaction is developed, in order to take into account bending-warping torsion interaction for symmetrical double T cross-sections (IP and HE steel profiles). Such formulation overcomes the overly conservative approach stated in EN 1993-1-1, for Class 1 and Class 2 cross-sections (plastic and compact cross-sections). Finally, a rigorous method for the determination of the bending resistance of cross-sections is proposed, considering the interaction with shear and torsion. The proposal is well suited to the concept of cross-sectional class and it is perfectly consistent with the approaches set out to consider the bending-shear and bending-warping torsion interactions.Peer ReviewedPostprint (author's final draft

Kinship Verification from Videos using Spatio-Temporal Texture Features and Deep Learning

Automatic kinship verification using facial images is a relatively new and challenging research problem in computer vision. It consists in automatically predicting whether two persons have a biological kin relation by examining their facial attributes. While most of the existing works extract shallow handcrafted features from still face images, we approach this problem from spatio-temporal point of view and explore the use of both shallow texture features and deep features for characterizing faces. Promising results, especially those of deep features, are obtained on the benchmark UvA-NEMO Smile database. Our extensive experiments also show the superiority of using videos over still images, hence pointing out the important role of facial dynamics in kinship verification. Furthermore, the fusion of the two types of features (i.e. shallow spatio-temporal texture features and deep features) shows significant performance improvements compared to state-of-the-art methods.Comment: 7 page

Intention prediction for interactive navigation in distributed robotic systems

Modern applications of mobile robots require them to have the ability to safely and effectively navigate in human environments. New challenges arise when these robots must plan their motion in a human-aware fashion. Current methods addressing this problem have focused mainly on the activity forecasting aspect, aiming at improving predictions without considering the active nature of the interaction, i.e. the robot’s effect on the environment and consequent issues such as reciprocity. Furthermore, many methods rely on computationally expensive offline training of predictive models that may not be well suited to rapidly evolving dynamic environments. This thesis presents a novel approach for enabling autonomous robots to navigate socially in environments with humans. Following formulations of the inverse planning problem, agents reason about the intentions of other agents and make predictions about their future interactive motion. A technique is proposed to implement counterfactual reasoning over a parametrised set of light-weight reciprocal motion models, thus making it more tractable to maintain beliefs over the future trajectories of other agents towards plausible goals. The speed of inference and the effectiveness of the algorithms is demonstrated via physical robot experiments, where computationally constrained robots navigate amongst humans in a distributed multi-sensor setup, able to infer other agents’ intentions as fast as 100ms after the first observation. While intention inference is a key aspect of successful human-robot interaction, executing any task requires planning that takes into account the predicted goals and trajectories of other agents, e.g., pedestrians. It is well known that robots demonstrate unwanted behaviours, such as freezing or becoming sluggishly responsive, when placed in dynamic and cluttered environments, due to the way in which safety margins according to simple heuristics end up covering the entire feasible space of motion. The presented approach makes more refined predictions about future movement, which enables robots to find collision-free paths quickly and efficiently. This thesis describes a novel technique for generating "interactive costmaps", a representation of the planner’s costs and rewards across time and space, providing an autonomous robot with the information required to navigate socially given the estimate of other agents’ intentions. This multi-layered costmap deters the robot from obstructing while encouraging social navigation respectful of other agents’ activity. Results show that this approach minimises collisions and near-collisions, minimises travel times for agents, and importantly offers the same computational cost as the most common costmap alternatives for navigation. A key part of the practical deployment of such technologies is their ease of implementation and configuration. Since every use case and environment is different and distinct, the presented methods use online adaptation to learn parameters of the navigating agents during runtime. Furthermore, this thesis includes a novel technique for allocating tasks in distributed robotics systems, where a tool is provided to maximise the performance on any distributed setup by automatic parameter tuning. All of these methods are implemented in ROS and distributed as open-source. The ultimate aim is to provide an accessible and efficient framework that may be seamlessly deployed on modern robots, enabling widespread use of intention prediction for interactive navigation in distributed robotic systems

A Cyberpunk 2077 perspective on the prediction and understanding of future technology

Science fiction and video games have long served as valuable tools for envisioning and inspiring future technological advancements. This position paper investigates the potential of Cyberpunk 2077, a popular science fiction video game, to shed light on the future of technology, particularly in the areas of artificial intelligence, edge computing, augmented humans, and biotechnology. By analyzing the game's portrayal of these technologies and their implications, we aim to understand the possibilities and challenges that lie ahead. We discuss key themes such as neurolink and brain-computer interfaces, multimodal recording systems, virtual and simulated reality, digital representation of the physical world, augmented and AI-based home appliances, smart clothing, and autonomous vehicles. The paper highlights the importance of designing technologies that can coexist with existing preferences and systems, considering the uneven adoption of new technologies. Through this exploration, we emphasize the potential of science fiction and video games like Cyberpunk 2077 as tools for guiding future technological advancements and shaping public perception of emerging innovations.Comment: 12 pages, 7 figure

Neotropical felid specimens at the Museu Paraense Emilio Goeldi: species, distribution, and morphometric data

Museu Paraense Emilio Goeldi (MPEG), situated at Brazilian state of Pará, houses the third largest South-American mammal scientific collection, being a primary source of information for the study of Amazonian and Neotropical mammalians. The collection holds 245 felid specimens, comprising 210 skulls, 53 skins, 10 skeletons, and two anatomical pieces, representing 90% of wild Brazilian cat species, mainly from localities of Northern Brazil. We presented a list of this material, indexed by the genera and species. We also provided craniodental measurements of all the specimens with skull, and comment on the conservation status of the species and other remarkable data, including the first record of Leopardus tigrinus in the Brazilian state of Rondônia

Localization of the thermosensitive X-prolyl dipeptidyl aminopeptidase in the vacuolar membrane of Saccharomyces cerevisiae

AbstractMost of the X-prolyl dipeptidyl aminopeptidase activity of Saccharomyces cerevisiae was found to be associated with purified vacuolar membranes (specific activity approx. 75-times higher than in the protoplast lysate). The tonoplast-bound enzyme is thermosensitive. Another heat-resistant enzyme was found in the protoplast lysate. The tonoplast-bound thermosensitive enzyme shows an apparent Km of 0.06 mM against L-alanyl-L-prolyl-p-nitroanilide while the heat-resistant enzyme shows an apparent Km of 0.4 mM against the same substrate

Neotropical felid specimens at the Museu Paraense Emilio Goeldi: species, distribution, and morphometric data

Museu Paraense Emilio Goeldi (MPEG), situated at Brazilian state of Pará, houses the third largest South-American mammal scientific collection, being a primary source of information for the study of Amazonian and Neotropical mammalians. The collection holds 245 felid specimens, comprising 210 skulls, 53 skins, 10 skeletons, and two anatomical pieces, representing 90% of wild Brazilian cat species, mainly from localities of Northern Brazil. We presented a list of this material, indexed by the genera and species. We also provided craniodental measurements of all the specimens with skull, and comment on the conservation status of the species and other remarkable data, including the first record of Leopardus tigrinus in the Brazilian state of Rondônia