The difficult alliance between vegan parents and pediatrician: A case report

The number of children on a vegetarian or vegan diet is gradually increasing. If not balanced and adequately supplemented, these dietary regimes can seriously impact the growth of children. Often the pediatrician is not perceived as a figure to rely on in the event of parents’ willingness to follow an alternative diet for their child. The feeling of distrust of parents towards the pediatrician can be dangerous for the health of the child. We present a 22-month-old boy with failure to thrive probably induced by an unbalanced vegetarian diet. The acquisition of the anamnestic data concerning the child’s diet was difficult because initially omitted by the parents. The poor compliance and the difficult follow-up highlights the difficulty in establishing a therapeutic alliance between parents who follow alternative regimens and the pediatrician

Geometric feature analysis for the classification of cultural heritage point clouds

In the last years, the application of artificial intelligence (Machine Learning and Deep Learning methods) for the classification of 3D point clouds has become an important task in modern 3D documentation and modelling applications. The identification of proper geometric and radiometric features becomes fundamental to classify 2D/3D data correctly. While many studies have been conducted in the geospatial field, the cultural heritage sector is still partly unexplored. In this paper we analyse the efficacy of the geometric covariance features as a support for the classification of Cultural Heritage point clouds. To analyse the impact of the different features calculated on spherical neighbourhoods at various radius sizes, we present results obtained on four different heritage case studies using different features configurations

Bloodied Hearts and Bawdy Planets: Greco-Roman Astrology and the Regenerative Force of the Feminine in Shakespeare’s \u3ci\u3eThe Winter’s Tale\u3c/i\u3e

This thesis offers a new reading of William Shakespeare’s late play The Winter’s Tale (1623), positing that in order to understand this complex and eccentric work, we must read it with a complex and eccentric eye. In The Winter’s Tale, planets strike without warning, pulling at hearts, wombs, and blood, impacting the health and emotional experience of characters in the play. This work is renowned for its inconsistent formal structure; the first half is a tragedy set in winter, but abruptly shifts to a comedy set in spring/summer in its latter half. What’s more, is that planets, luminaries, and stars above constantly interfere with human life, due to their gravitational pull. I argue that in order to fully comprehend The Winter’s Tale and all its nuance, one must read it with an understanding of Renaissance astrology, a science that was fully embedded in Shakespeare’s cultural milieu. The astrological worldview accepts that the motion of planets in the heavens impact life on earth, and this is crystallized in the Renaissance belief of micro- and macrocosmic interplay. By tracing planetary language in The Winter’s Tale, we find a deeper reading of the play\u27s gender dynamics than previous scholarship has offered. The Winter\u27s Tale\u27s central focus is Leontes, king of Sicilia, who believes his wife has committed adultery. This launches him into unwarranted fits of misogynistic destruction, inadvertently instigating the seeming death of his family and other tragic events. Shakespeare drew richly, in all of his works, from Greco-Roman myth, Greek drama, and history, and embedded in all of those disciplines is the biopolitics of the polis. Classical Athenian culture purposefully limited the rights of women, who were thought to lack emotional control, in comparison to men. The Renaissance was a moment of cultural rebirth, heavily influenced by classical Greek cultural materials, of which astrology was much a part. Astrology colored Renaissance ideas about the body and gender, and thus is instrumental in deepening our understanding of this eccentric play. Reading The Winter’s Tale with astrological awareness offers a new reading of the play’s gender dynamics, and shows that Shakespeare was lampooning the acts of tyrants who fear the regenerative power of feminine agency

Knowledge and valorization of historical sites through 3D documentation and modeling

The paper presents the first results of an interdisciplinary project related to the 3D documentation, dissemination, valorization and digital access of archeological sites. Beside the mere 3D documentation aim, the project has two goals: (i) to easily explore and share via web references and results of the interdisciplinary work, including the interpretative process and the final reconstruction of the remains; (ii) to promote and valorize archaeological areas using reality-based 3D data and Virtual Reality devices. This method has been verified on the ruins of the archeological site of Pausilypon, a maritime villa of Roman period (Naples, Italy). Using Unity3D, the virtual tour of the heritage site was integrated and enriched with the surveyed 3D data, text documents, CAAD reconstruction hypotheses, drawings, photos, etc. In this way, starting from the actual appearance of the ruins (panoramic images), passing through the 3D digital surveying models and several other historical information, the user is able to access virtual contents and reconstructed scenarios, all in a single virtual, interactive and immersive environment. These contents and scenarios allow to derive documentation and geometrical information, understand the site, perform analyses, see interpretative processes, communicate historical information and valorize the heritage location

SPARSE POINT CLOUD FILTERING BASED ON COVARIANCE FEATURES

Abstract. This work presents an extended photogrammetric pipeline aimed to improve 3D reconstruction results. Standard photogrammetric pipelines can produce noisy 3D data, especially when images are acquired with various sensors featuring different properties. In this paper, we propose an automatic filtering procedure based on some geometric features computed on the sparse point cloud created within the bundle adjustment phase. Bad 3D tie points and outliers are detected and removed, relying on micro and macro-clusters analyses. Clusters are built according to the prevalent dimensionality class (1D, 2D, 3D) assigned to low-entropy points, and corresponding to the main linear, planar o scatter local behaviour of the point cloud. While the macro-clusters analysis removes smallsized clusters and high-entropy points, in the micro-clusters investigation covariance features are used to verify the inner coherence of each point to the assigned class. Results on heritage scenarios are presented and discussed.</p

A semi-automated approach to model architectural elements in Scan-to-BIM processes

In the last years, the AEC (Architecture, Engineering and Construction) domain has exponentially increased the use of BIM and HBIM models for several applications, such as planning renovation and restoration, building maintenance, cost managing, or structural/energetic retrofit design. However, obtaining detailed as-built BIM models is a demanding and time-consuming process. Especially in historical contexts, many different and complex architectural elements need to be carefully and manually modelled. Meshes or surfaces and NURBS or polylines, derived from 3D reality-based data, are recently used as a reference for the HBIM accurate modelling. This work proposes a comprehensive and novel semi-automated approach to reconstruct architectural elements through the Visual Programming Language (VPL) Dynamo software and a Boundary-Representation method (B-rep), starting from 3D surveying data and point clouds classification. A wide package of scripts provides solutions for modelling complex shapes and transferring the obtained 3D models into BIM Authoring tools for a complete reconstruction phase. The presented procedure, useful for different BIM or HBIM applications, proved to reduce the modelling time significantly

FROM 3D SURVEYING DATA TO BIM TO BEM: THE INCUBE DATASET

In recent years, the improvement of sensors and methodologies for 3D reality-based surveying has exponentially enhanced the possibility of creating digital replicas of the real world. LiDAR technologies and photogrammetry are currently standard approaches for collecting 3D geometric information of indoor and outdoor environments at different scales. This information can potentially be part of a broader processing workflow that, starting from 3D surveyed data and through Building Information Models (BIM) generation, leads to more complex analyses of buildings&rsquo; features and behavior (Figure 1). However, creating BIM models, especially of historic and heritage assets (HBIM), is still resource-intensive and time-consuming due to the manual efforts required for data creation and enrichment. Improve 3D data processing, interoperability, and the automation of the BIM generation process are some of the trending research topics, and benchmark datasets are extremely helpful in evaluating newly developed algorithms and methodologies for these scopes. This paper introduces the InCUBE dataset, resulting from the activities of the recently funded EU InCUBE project, focused on unlocking the EU building renovation through integrated strategies and processes for efficient built-environment management (including the use of innovative renewable energy technologies and digitalization). The set of data collects raw and processed data produced for the Italian demo site in the Santa Chiara district of Trento (Italy). The diversity of the shared data enables multiple possible uses, investigations and developments, and some of them are presented in this contribution

BENCHMARKING THE EXTRACTION OF 3D GEOMETRY FROM UAV IMAGES WITH DEEP LEARNING METHODS

3D reconstruction from single and multi-view stereo images is still an open research topic, despite the high number of solutions proposed in the last decades. The surge of deep learning methods has then stimulated the development of new methods using monocular (MDE, Monocular Depth Estimation), stereoscopic and Multi-View Stereo (MVS) 3D reconstruction, showing promising results, often comparable to or even better than traditional methods. The more recent development of NeRF (Neural Radial Fields) has further triggered the interest for this kind of solution. Most of the proposed approaches, however, focus on terrestrial applications (e.g., autonomous driving or small artefacts 3D reconstructions), while airborne and UAV acquisitions are often overlooked. The recent introduction of new datasets, such as UseGeo has, therefore, given the opportunity to assess how state-of-the-art MDE, MVS and NeRF 3D reconstruction algorithms perform using airborne UAV images, allowing their comparison with LiDAR ground truth. This paper aims to present the results achieved by two MDE, two MVS and two NeRF approaches levering deep learning approaches, trained and tested using the UseGeo dataset. This work allows the comparison with a ground truth showing the current state of the art of these solutions and providing useful indications for their future development and improvement

Nerf for heritage 3d reconstruction

Conventional or learning-based 3D reconstruction methods from images have clearly shown their potential for 3D heritage documentation. Nevertheless, Neural Radiance Field (NeRF) approaches are recently revolutionising the way a scene can be rendered or reconstructed in 3D from a set of oriented images. Therefore the paper wants to review some of the last NeRF methods applied to various cultural heritage datasets collected with smartphone videos, touristic approaches or reflex cameras. Firstly several NeRF methods are evaluated. It turned out that Instant-NGP and Nerfacto methods achieved the best outcomes, outperforming all other methods significantly. Successively qualitative and quantitative analyses are performed on various datasets, revealing the good performances of NeRF methods, in particular for areas with uniform texture or shining surfaces, as well as for small datasets of lost artefacts. This is for sure opening new frontiers for 3D documentation, visualization and communication purposes of digital heritage