Estudio mineralógico, textural y físico-mecánico de morteros de cal hidráulica curados en distintas condiciones de humedad relativa

This work focuses on the chemical-mineralogical, textural and physical-mechanical properties of hydraulic lime mortars made with siliceous and calcareous aggregate. Mortars were cured at 60% and 90% of relative humidity, so as to assess the variability of mortar petrophysical properties in the hardened state due to the moisture conditions. The final aim was to determine the most adequate moisture conditions to be maintained during application and hardening of hydraulic mortars intended for repair interventions. We found out that using a calcareous aggregate and curing mortar at 90% of relative humidity give place to better textural and mechanical properties. However, these characteristics mostly depend on the maximum size of the aggregate grains, which should be smaller than 6 mm, in order to avoid the occurrence of mechanical discontinuities in the mortar.En este trabajo se han estudiado las propiedades químico-mineralógicas, texturales y físico-mecánicas de morteros de cal hidráulica elaborados con áridos silíceo y calcítico. Estos morteros se han curado al 60% y 90% de humedad relativa, con el fin de evaluar las eventuales diferencias en las propiedades petrofísicas de los morteros una vez endurecidos y así establecer cuál de los dos ambientes es recomendable durante la aplicación y fraguado de morteros de cal hidráulica destinados a obras de restauración. Se ha encontrado que el uso de un árido de composición calcítica y el curado al 90% de humedad relativa dan lugar a morteros hidráulicos con mejores características texturales y propiedades mecánicas. De todas formas, estas características dependen principalmente del tamaño máximo del árido empleado, que debería ser inferior a 6 mm para evitar discontinuidades mecánicas en el mortero

JULIE GIROUX’S SYMPHONY NO. 6: THE BLUE MARBLE BACKGROUND, ANALYSIS, AND CONDUCTOR’S GUIDE

Julie Giroux’s Symphony No. 6: The Blue Marble (2022) is an original work for wind band that is quickly rising in popularity among instrumental conductors and ensembles throughout the world. The purposes of this document are to 1) provide biographical details regarding Julie Giroux and her musical career; 2) provide a background of the work’s conception from a musical and multi-media perspective through interviews with Giroux and the first conductors of the work; 3) provide a multi-parametric structural analysis of the work and its companion film; 4) provide conductors with useful information for programming and rehearsing the work. Chapter one discusses biographical and historical details regarding Giroux and Symphony No. 6 that provide context for better understanding of the work. Chapter two, three, and four contain structural analysis that dissect elements of form, melodic structure, harmonic structure, textural structure, orchestration structure, rhythmic structure, temporal structure, and other important elements in movements 1, 2, and 3, respectively. Chapter five provides further context of The Blue Marble companion film alongside a thematic analysis of the film’s scenes. Chapter six provides useful information for conductors who plan to program the Symphony. An appendix of information provides further insight of the Symphony through interviews with composer Julie Giroux, and leading wind conductors Brad Genevro and Lowell Graham

Application-aware optimization of Artificial Intelligence for deployment on resource constrained devices

Artificial intelligence (AI) is changing people's everyday life. AI techniques such as Deep Neural Networks (DNN) rely on heavy computational models, which are in principle designed to be executed on powerful HW platforms, such as desktop or server environments. However, the increasing need to apply such solutions in people's everyday life has encouraged the research for methods to allow their deployment on embedded, portable and stand-alone devices, such as mobile phones, which exhibit relatively low memory and computational resources. Such methods targets both the development of lightweight AI algorithms and their acceleration through dedicated HW. This thesis focuses on the development of lightweight AI solutions, with attention to deep neural networks, to facilitate their deployment on resource constrained devices. Focusing on the computer vision field, we show how putting together the self learning ability of deep neural networks with application-specific knowledge, in the form of feature engineering, it is possible to dramatically reduce the total memory and computational burden, thus allowing the deployment on edge devices. The proposed approach aims to be complementary to already existing application-independent network compression solutions. In this work three main DNN optimization goals have been considered: increasing speed and accuracy, allowing training at the edge, and allowing execution on a microcontroller. For each of these we deployed the resulting algorithm to the target embedded device and measured its performance

Variational methods and its applications to computer vision

Many computer vision applications such as image segmentation can be formulated in a ''variational'' way as energy minimization problems. Unfortunately, the computational task of minimizing these energies is usually difficult as it generally involves non convex functions in a space with thousands of dimensions and often the associated combinatorial problems are NP-hard to solve. Furthermore, they are ill-posed inverse problems and therefore are extremely sensitive to perturbations (e.g. noise). For this reason in order to compute a physically reliable approximation from given noisy data, it is necessary to incorporate into the mathematical model appropriate regularizations that require complex computations. The main aim of this work is to describe variational segmentation methods that are particularly effective for curvilinear structures. Due to their complex geometry, classical regularization techniques cannot be adopted because they lead to the loss of most of low contrasted details. In contrast, the proposed method not only better preserves curvilinear structures, but also reconnects some parts that may have been disconnected by noise. Moreover, it can be easily extensible to graphs and successfully applied to different types of data such as medical imagery (i.e. vessels, hearth coronaries etc), material samples (i.e. concrete) and satellite signals (i.e. streets, rivers etc.). In particular, we will show results and performances about an implementation targeting new generation of High Performance Computing (HPC) architectures where different types of coprocessors cooperate. The involved dataset consists of approximately 200 images of cracks, captured in three different tunnels by a robotic machine designed for the European ROBO-SPECT project.Open Acces

Improving the monitoring and evaluation of schistosomiasis by determining appropriate targets and utilizing new technologies

The World Health Organization’s framework for the assessment of schistosomiasis morbidity control utilizes the prevalence of heavy-intensity infections in a homogenous ecological zone. The foundational research for the use of heavy-intensity infections is at least 30 years old. Research since then has illuminated the relationship between Schistosoma infection and all morbidity. In addition, severe, chronic, schistosomiasis morbidity is less common due to increasing dissemination of preventive chemotherapy. There are calls for improvements to the monitoring and evaluation framework, especially relating to the measurement of schistosomiasis morbidity. The focus of this thesis was to improve the schistosomiasis monitoring and evaluation framework by evaluating whether those current infection measures are linked to morbidity indicators. For those measures linked to indicators, an attempt was made to calculate programmatic targets linked to morbidity using robust methods. Targets based on microhaematuria prevalence were calculated based on community-level S. haematobium prevalence. For S. mansoni, associations between infection and morbidity were much weaker and it appears unlikely that a reliable target can be found. S. mansoni morbidity control may require changes to accurately measure the S. mansoni morbidity burden in a geographic area. Incorporating new technologies, such as portable, tablet-based ultrasound systems, may allow researchers and control programs to collect schistosomiasis morbidity indicators

Current airframe manufacturing technologies in the aeronautical industry and trends for future developments

The aeronautical industry is an area in constant change. The aircraft as a product is evolving, making use, most of the times, of new revolutionary materials and manufacturing processes. At the same time, the global market is expanding quickly and new players are entering the market in increasing competition. At this point, it is, thus important to analyze the options that manufacturers have at their disposal to tackle with this new environment. Having this in mind, this work aimed at assessing the current manufacturing technologies, focused on the biggest part of the aircraft, the airframe, analyzing in particular the application of composite materials and lightweight metal alloys and their implications in production and operations. In this scope, the current state and future trends of materials, environmental sustainability, processes, joining, repairing and inspection methods, are assessed, always from the point of view of the design, taking into account the advantages and disadvantages of composite materials and of the lightweight metal alloys, as well as the obstacles to their development and application. When analyzing the future trends in material’s application, a study is presented to quantify those trends for the most important materials in aircraft construction, from which conclusions were derived covering aspects related with the evolution of the mix of materials, in the years to come, in what aircraft construction is concerned, based on historical data from a substantial collection of aircraft data