Planewave density interpolation methods for 3D Helmholtz boundary integral equations

This paper introduces planewave density interpolation methods for the regularization of weakly singular, strongly singular, hypersingular and nearly singular integral kernels present in 3D Helmholtz surface layer potentials and associated integral operators. Relying on Green's third identity and pointwise interpolation of density functions in the form of planewaves, these methods allow layer potentials and integral operators to be expressed in terms of integrand functions that remain smooth (at least bounded) regardless the location of the target point relative to the surface sources. Common challenging integrals that arise in both Nystr\"om and boundary element discretization of boundary integral equation, can then be numerically evaluated by standard quadrature rules that are irrespective of the kernel singularity. Closed-form and purely numerical planewave density interpolation procedures are presented in this paper, which are used in conjunction with Chebyshev-based Nystr\"om and Galerkin boundary element methods. A variety of numerical examples---including problems of acoustic scattering involving multiple touching and even intersecting obstacles, demonstrate the capabilities of the proposed technique

Harmonic density interpolation methods for high-order evaluation of Laplace layer potentials in 2D and 3D

We present an effective harmonic density interpolation method for the numerical evaluation of singular and nearly singular Laplace boundary integral operators and layer potentials in two and three spatial dimensions. The method relies on the use of Green's third identity and local Taylor-like interpolations of density functions in terms of harmonic polynomials. The proposed technique effectively regularizes the singularities present in boundary integral operators and layer potentials, and recasts the latter in terms of integrands that are bounded or even more regular, depending on the order of the density interpolation. The resulting boundary integrals can then be easily, accurately, and inexpensively evaluated by means of standard quadrature rules. A variety of numerical examples demonstrate the effectiveness of the technique when used in conjunction with the classical trapezoidal rule (to integrate over smooth curves) in two-dimensions, and with a Chebyshev-type quadrature rule (to integrate over surfaces given as unions of non-overlapping quadrilateral patches) in three-dimensions

Unemployment and entrepreneurship: a cyclical relationship?

This paper presents a cyclical model for unemployment and entrepreneurship. The estimated periodicity of the cycles for the US, the UK, Spain and Ireland is between 5 and 10 years, and the orders of integration are smaller (greater) than 1 if the underlying disturbances are autocorrelated (white noise), corresponding to dampen cycles (limit cycle).New firms, Employment creation, cycles.

Fault tolerant decentralized deep neural networks

Dissertação de mestrado integrado em Informatics EngineeringMachine Learning is trending in computer science, especially Deep Learning. Training algorithms that follow this approach to Machine Learning routinely deal with vast amounts of data. Processing these enormous quantities of data requires complex computation tasks that can take a long time to produce results. Distributing computation efforts across multiple machines makes sense in this context, as it allows conclusive results to be available in a shorter time frame. Distributing the training of a Deep Neural Network is not a trivial procedure. Various architectures have been proposed, following two different paradigms. The most common one follows a centralized approach, where a centralized entity, broadly named parameter server, synchronizes and coordinates the updates generated by a number of workers. The alternative discards the centralized unit, assuming a decentralized architecture. The synchronization between the multiple workers is assured by communication techniques that average gradients between a node and its peers. High-end clusters are the ideal environment to deploy Deep Learning systems. Low latency between nodes assures low idle times for workers, increasing the overall system performance. These setups, however, are expensive and are only available to a limited number of entities. On the other end, there is a continuous growth of edge devices with potentially vast amounts of available computational resources. In this dissertation, we aim to implement a fault tolerant decentralized Deep Neural Net work training framework, capable of handling the high latency and unreliability characteristic of edge networks. To manage communication between nodes, we employ decentralized algorithms capable of estimating parameters globallyMachine Learning, mais especificamente Deep Learning, é um campo emergente nas ciências da computação. Algoritmos de treino aplicados em Deep Learning lidam muito frequentemente com vastas quantidades de dados. Processar estas enormes quantidades de dados requer operações computacionais complexas que demoram demasiado tempo para produzir resultados. Distribuir o esforço computacional por múltiplas máquinas faz todo o sentido neste contexto e permite um aumento significativo de desempenho. Distribuir o método de treino de uma rede neuronal não é um processo trivial. Várias arquiteturas têm sido propostas, seguindo dois diferentes paradigmas. O mais comum segue uma abordagem centralizada, onde uma entidade central, normalmente denominada de parameter server, sincroniza e coordena todas as atualizações produzidas pelos workers. A alternativa passa por descartar a entidade centralizada, assumindo uma arquitetura descentralizada. A sincronização entre workers é assegurada através de estratégias de comunicação descentralizadas. Clusters de alta performance são o ambiente ideal para a implementação de sistemas de Deep Learning. A baixa latência entre nodos assegura baixos períodos de inatividade nos workers, aumentando assim o rendimento do sistema. Estas instalações, contudo, são muito custosas, estando apenas disponíveis para um pequeno número de entidades. Por outro lado, o número de equipamentos nas extremidades da rede, com baixo aproveitamento de poder computacional, continua a crescer, o que torna o seu uso desejável. Nesta dissertação, visamos implementar um ambiente de treino de redes neuronais descentralizado e tolerante a faltas, apto a lidar com alta latência nas comunicações e baixa estabilidade nos nodos, caraterística de redes na extremidade. Para coordenar a comunicação entre os nodos, empregamos algoritmos de agregação, capazes de criar uma visão geral de parâmetros numa topologia

Forming Next-Generation Antibody-Nanoparticle Conjugates through the Oriented Installation of Antibody Fragments

Use of antibody-nanoparticle conjugates (ANCs) has emerged as a multi-disciplinary strategy for combating cancer - they combine the versatility of nanoparticles and the potential to deliver cargo to cancer cells with the high targeting specificity of surface antibodies to recognise specific biomarkers that are expressed in cancer cells. Several strategies have been employed to graft nanoparticles to antibodies, however, most of them rely on fragile non-covalent interactions or on methods that do not exert control on antibody paratope orientation (e.g. random modification of multiple lysine residues on antibodies). These issues greatly limit ANCs antigen binding capability, reproducibility and, thus, overall efficacy. In this thesis, alternatives strategies of generating ANCs are proposed, regarding antibody orientation on the nanoparticles’ surface through the use of pyridazinedione-based linkers that site-selectively modify disulfide(s) on antibodies. The overall aim is to achieve highly-controlled ANC construction so that these next-generation ANCs can be employed in future cancer treatments. In Chapter 1, an introduction to current protein modification techniques is presented and, in a more biological context, the structure and use of full antibodies and antibody fragments is described. Additionally, an overview of the current biomedical applications of numerous different types of inorganic and organic nanoparticles is introduced. In Chapter 2, the creation of antibody fragment Fab targeted PEG-PLGA nanoparticles is reported. In particular, the generation of Trastuzumab Fab fragments via digestion techniques and a new approach for their attachment to PEG-PLGA nanoparticles and the consequent results of improved antigen binding are described. In Chapters 3 and 4, different proteins are employed for the generation of ANCs, namely Cetuximab Fab (in which cell studies are also performed) and considerably smaller proteins such as variable new antigen receptors (VNARs) via a similar methodology to that employed in Chapter 2. Concluding, an overview of achieved results and future work are covered

Information management and social networks in organizational innovation networks

Tese de mestrado. Ciência da Informação. Faculdade de Engenharia. Universidade do Porto. 201

Persistence on airline accidents

This paper analyses airline accidents data from 1927-2006. The fractional integration methodology is adopted. It is shown that airline accidents are persistent and (fractionally) cointegrated with airline traffic. Thus, there exists an equilibrium relation between air accidents and airline traffic, with the effect of the shocks to that relationship disappearing in the long run. Policy implications are derived for countering accidents events.

Persistence in Airline Accidents

This paper analyses airline accident data from 1927-2006, through fractional integration. It is shown that airline accidents are persistent and (fractionally) cointegrated with airline traffic. There exists a negative relation between air accidents and airline traffic, with the effect of the shocks to that relationship disappearing in the long run. Policy implications are derived for countering accident events.Accidents; airline; Time series; Persistence; Long memory; Cointegration.

Brazilian Land Tenure and Conflicts: The Landless Peasants' Movement

This paper analyzes conflicts and violence in Brazil involving landless peasants occupying privately-owned land, for the period 2000-2008. It is the first study to be undertaken at a national level, with a contemporary data span, using a count data model that allows for heterogeneity, endogeneity and dynamics. Results from the estimated model show that the violent land occupation grows with left-wing political support for land occupation, rural population density, and agricultural credit, and decreases with poverty, agricultural productivity. The study discusses the interconnection of land reform, poverty and conflict.Land occupation, land reform, Brazil, poverty, conflict.