An Algorithm for Grouping Lines Which Converge to Vanishing Points in Perspective Sketches of Polyhedra

We seek to detect the vanishing points implied by design sketches of engineering products. Adapting previous ap- proaches, developed in computer vision for analysis of vectorised photographic images, is unsatisfactory, as they do not allow for the inherent imperfection of sketches. Human perception seems not to be disturbed by such imperfections. Hence, we have de- signed and implemented a vanishing point detection algorithm which mimics the human perception process and tested it with perspective line drawings derived from engineering sketches of polyhedral objects. The new algorithm is fast, easily- implemented, returns the approximate locations of the main vanishing points and identifies those groups of lines in 2D which correspond to groups of parallel edges in the 3D object

Limit analysis of reinforced masonry vaults

Reinforced brick masonry has experienced only scarce use as a fully structural material due to, among other reasons, the lack of design criteria and calculation tools allowing a scientific, but also practical, engineering approach to design and assessment. Aiming at contributing to a more widespread use of this material, a simplified method for the ultimate analysis of reinforced masonry arches and cylindrical vaults, based on the lower-bound theorem (or static approach) of plasticity, has been developed. This approach has been satisfactorily validated by comparison with experimental and numerical results obtained by more accurate numerical models

Deep Learning for Vanishing Point Detection Using an Inverse Gnomonic Projection

We present a novel approach for vanishing point detection from uncalibrated monocular images. In contrast to state-of-the-art, we make no a priori assumptions about the observed scene. Our method is based on a convolutional neural network (CNN) which does not use natural images, but a Gaussian sphere representation arising from an inverse gnomonic projection of lines detected in an image. This allows us to rely on synthetic data for training, eliminating the need for labelled images. Our method achieves competitive performance on three horizon estimation benchmark datasets. We further highlight some additional use cases for which our vanishing point detection algorithm can be used.Comment: Accepted for publication at German Conference on Pattern Recognition (GCPR) 2017. This research was supported by German Research Foundation DFG within Priority Research Programme 1894 "Volunteered Geographic Information: Interpretation, Visualisation and Social Computing

Deep panoramic depth prediction and completion for indoor scenes

We introduce a novel end-to-end deep-learning solution for rapidly estimating a dense spherical depth map of an indoor environment. Our input is a single equirectangular image registered with a sparse depth map, as provided by a variety of common capture setups. Depth is inferred by an efficient and lightweight single-branch network, which employs a dynamic gating system to process together dense visual data and sparse geometric data. We exploit the characteristics of typical man-made environments to efficiently compress multi-resolution features and find short- and long-range relations among scene parts. Furthermore, we introduce a new augmentation strategy to make the model robust to different types of sparsity, including those generated by various structured light sensors and LiDAR setups. The experimental results demonstrate that our method provides interactive performance and outperforms state-of-the-art solutions in computational efficiency, adaptivity to variable depth sparsity patterns, and prediction accuracy for challenging indoor data, even when trained solely on synthetic data without any fine tuning. (Figure presented.

Adolescents' mental health problems increase after parental divorce, not before, and persist until adulthood:a longitudinal TRAILS study

Parental divorce is one of the most stressful life events for youth and is often associated with (long-lasting) emotional and behavioral problems (EBP). However, not much is known about the timing of the emergence of these EBP in adolescents relative to the moment of parental divorce, and its longitudinal effects. We therefore assessed this timing of EBP in adolescents of divorce and its longitudinal effects. We used the first four waves of the TRacking Adolescent's Individual Lives Survey (TRAILS) cohort, which included 2230 10-12 years olds at baseline. EBP were measured through the Youth Self-Report (YSR), as internalizing and externalizing problems. We applied multilevel analysis to assess the effect of divorce on EBP. The levels of both internalizing and externalizing problems were significantly higher in the period after parental divorce (beta = 0.03, and 0.03, respectively; p <0.05), but not in the period before divorce, with a persistent and increasing effect over the follow-up periods compared to adolescents not experiencing divorce. Adolescents tend to develop more EBP in the period after parental divorce, not before. These effects are long-lasting and underline the need for better care for children with divorcing parents

GARCÍA MARQUÉS, A. (2019). Pensando el sujeto: Aristóteles y Quine. Madrid: Dykinson

Reseña de: GARCÍA MARQUÉS, A. (2019). Pensando el sujeto: Aristóteles y Quine. Madrid: Dykinson

Relationships between spawn quality and biochemical composition of eggs and hatchlings of Octopus vulgaris under different parental diets

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Growth and survival of cuttlefish (Sepia officinalis) of different ages fed crustaceans and fish. Effects of frozen and live prey

Three feeding experiments, using live mysid shrimp, grass shrimp or fish fry as prey for 1-, 30- and 60-day-old cuttlefish were conducted to determine the efficiency of each dietary source in relation to cuttlefish size and age. Additionally, a fourth experiment using fish fry and grass shrimp, but previously frozen, was also conducted. The results showed that when 1-day-old cuttlefish were fed mysids, grass shrimp or fish for 4 weeks, mysids were the best prey, but only during the first week. From this moment until the end of the experiment, the best growth rate was when cuttlefish were fed grass shrimp. Cuttlefish fed fish fry showed the poorest growth rate throughout the experiment. Similarly, cuttlefish aged 30 or 60 days fed grass shrimp or fish fry had the best growth rates when fed grass shrimp. When cuttlefish were fed live fish, survival increased with size of cuttlefish (73.3%, 91.7% and 100% for 1, 30 and 60 days cuttlefish, respectively). In the fourth experiment, using frozen diets, overall acceptance of each diet (feeding rates) was the same for fish and shrimp. However, lower growth was obtained when cuttlefish were fed fish compared to grass shrimp. This lower growth was due to a lower food conversion (28% vs. 41%). Since cephalopod paralarvae and juvenile most likely need prey rich in polyunsaturated fatty acids (PUFA), phospholipids and cholesterol, and a moderate content in neutral lipids, we have analyzed the biochemical compositions of the different prey to evaluate the influence of this factor on growth and survival.En prensa2,04