Brownian motion in a truncated Weyl chamber

We examine the non-exit probability of a multidimensional Brownian motion from a growing truncated Weyl chamber. Different regimes are identified according to the growth speed, ranging from polynomial decay over stretched-exponential to exponential decay. Furthermore we derive associated large deviation principles for the empirical measure of the properly rescaled and transformed Brownian motion as the dimension grows to infinity. Our main tool is an explicit eigenvalue expansion for the transition probabilities before exiting the truncated Weyl chamber

Uma aplicação ao armamento portátil do Corpo de Fuzileiros

O presente trabalho surgiu da necessidade de melhoria do Sistema de Gestão de Stock implementado no Corpo de Fuzileiros. Tem por objetivo o desenho e edificação de um Sistema de Gestão de existências inovador, na forma de uma aplicação web, direcionado para o Armamento Portátil e seus acessórios. Este trabalho insere-se no âmbito da gestão logística de recursos, nomeadamente de armamento portátil e seus acessórios, tendo-se realizado uma Análise ABC que permitiu avaliar a relevância do material. Este procedimento faculta uma gestão mais eficiente do material existente, tendo em consideração o seu valor e criticidade operacional. O desenvolvimento do sistema informático de gestão assentou em dois softwares de base: o MongoDB, para a Base de Dados não relacional, e o Python (e as suas bibliotecas), para a edificação estrutural e gráfica, que, em conjunto, deram vida a este sistema de gestão. Foram implementadas diversas ferramentas e funcionalidades, que visam apoiar o utilizador no seu dia a dia, ao permitirem um controlo simples e eficaz dos artigos a gerir. É exemplo o conhecimento permanente da localização e estado de operacionalidade de todos os artigos, ou a possibilidade de incluir os documentos de suporte à movimentação e gestão do material. Outras ferramentas disponíveis são a emissão de fichas de inventário, essenciais no controlo de existências físicas regularmente levado a cabo nos paióis, ou o acesso a gráficos interativos que permitem adquirir, de forma rápida, a visão geral do material. Apesar da complexidade das tarefas a que dá resposta, o sistema proposto proporciona uma interface simples e intuitiva com o utilizador. Para além do caso para que foi otimizada, será possível, com os necessários ajustes, o seu alargamento a outras tipologias de material ou, implementação em outras unidades militares.This work arose from the need of improvement of the Stock Management System currently implemented at the unit Corpo de Fuzileiros. The main goals of this project were based on the design and construction of an innovative Stock Management System for Portable Armament. Considering the logistical nature of this project, an ABC Analysis of Logistic Data was initially carried out, from which it was possible to identify the most relevant stock units. The development of the application “Sistema de Gestão de Armamento Portátil” was based on two fundamental softwares: MongoDB, for the non-relational database, and Python (and its libraries) for structural and graphical development, which together brought this system to life. As a management system, several tools and functionalities have been implemented in this web application, which aim to support the user in their day-to-day tasks, by allowing a simple and effective control of the items to be managed. An example is the possibility of knowing the location and status of all items, through the insertion of different types of records in the application, together with their official documents. Other available tools are the issuance of inventory sheets, essential to assist the user in the control of physical stocks regularly carried out in the storerooms, or the access to interactive graphical charts that allows to acquire a quick overview of the material. Despite the complexity of the tasks to which it responds, the work developed in this thesis was, from the beginning, thought in a simple and intuitive way. In addition to its implementation in the Unit, this system has been developed to allow its expansion to the rest of the material of the Unit or even its implementation in other Units that would benefit from this Management System

Overcoming Missing and Incomplete Modalities with Generative Adversarial Networks for Building Footprint Segmentation

The integration of information acquired with different modalities, spatial resolution and spectral bands has shown to improve predictive accuracies. Data fusion is therefore one of the key challenges in remote sensing. Most prior work focusing on multi-modal fusion, assumes that modalities are always available during inference. This assumption limits the applications of multi-modal models since in practice the data collection process is likely to generate data with missing, incomplete or corrupted modalities. In this paper, we show that Generative Adversarial Networks can be effectively used to overcome the problems that arise when modalities are missing or incomplete. Focusing on semantic segmentation of building footprints with missing modalities, our approach achieves an improvement of about 2% on the Intersection over Union (IoU) against the same network that relies only on the available modality

On the use of a cascaded convolutional neural network for three-dimensional flow measurements using astigmatic PTV

Many applications in chemistry, biology and medicine use microfluidic devices to separate, detect and analyze samples on a miniaturized size-level. Fluid flows evolving in channels of only several tens to hundreds of micrometers in size are often of a 3D nature, affecting the tailored transport of cells and particles. To analyze flow phenomena and local distributions of particles within those channels, astigmatic particle tracking velocimetry (APTV) has become a valuable tool, on condition that basic requirements like low optical aberrations and particles with a very narrow size distribution are fulfilled. Making use of the progress made in the field of machine vision, deep neural networks may help to overcome these limiting requirements, opening new fields of applications for APTV and allowing them to be used by nonexpert users. To qualify the use of a cascaded deep convolutional neural network (CNN) for particle detection and position regression, a detailed investigation was carried out starting from artificial particle images with known ground truth to real flow measurements inside a microchannel, using particles with uni- and bimodal size distributions. In the case of monodisperse particles, the mean absolute error and standard deviation of particle depth-position of less than and about 1 [my]m were determined, employing the deep neural network and the classical evaluation method based on the minimum Euclidean distance approach. While these values apply to all particle size distributions using the neural network, they continuously increase towards the margins of the measurement volume of about one order of magnitude for the classical method, if nonmonodisperse particles are used. Nevertheless, limiting the depth of measurement volume in between the two focal points of APTV, reliable flow measurements with low uncertainty are also possible with the classical evaluation method and polydisperse tracer particles. The results of the flow measurements presented herein confirm this finding. The source code of the deep neural network used here is available on https://github.com/SECSY-Group/DNN-APTV

Species–area relationships on small islands differ among plant growth forms

Aim: We tested whether species–area relationships of small islands differ among plant growth forms and whether this influences the prevalence of the small-island effect (SIE). The SIE states that species richness on small islands is independent of island area or relates to area in a different way compared with larger islands. We investigated whether island isolation affects the limits of the SIE and which environmental factors drive species richness on small islands. Location: Seven hundred islands (< 100 km2) worldwide belonging to 17 archipelagos. Major taxa studied: Angiosperms. Methods: We applied linear and breakpoint species–area models for angiosperm species richness and for herb, shrub and tree species richness per archipelago separately, to test for the existence of SIEs. For archipelagos featuring the SIE, we calculated the island area at which the breakpoints occurred (breakpoint area) and used linear models to test whether the breakpoint areas varied with isolation. We used linear mixed-effect models to discern the effects of seven environmental variables related to island area, isolation and other environmental factors on the species richness of each growth form for islands smaller than the breakpoint area. Results: For 71% of all archipelagos, we found an SIE for total and herb species richness, and for 59% for shrub species richness and 53% for tree species richness. Shrub and tree species richness showed larger breakpoint areas than total and herb species richness. The breakpoint area was significantly positively affected by the isolation of islands within an archipelago for total and shrub species richness. Species richness on islands within the range of the SIE was differentially affected by environmental factors across growth forms. Main conclusion: The SIE is a widespread phenomenon that is more complex than generally described. Different functional groups have different environmental requirements that shape their biogeographical patterns and affect species–area and, more generally, richness–environment relationships. The complexity of these patterns cannot be revealed when measuring overall plant species richness.Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659Studienstiftung des Deutschen Volkes http://dx.doi.org/10.13039/501100004350Peer Reviewe