Previous research has shown that individuals endorsing inattention and hyperactivity-impulsivity have deficient performance on tasks tapping different aspects of attention. Although there is empirical evidence suggesting that the behavioral domains of inattention and hyperactivity-impulsivity are linked to functioning of independent and separate brain areas and neurotransmitter systems, cognitive characterization of adults presenting with problems within these domains is not complete. The aim for this study was to identify the cognitive correlates of the core behavioral domains that define the diagnosis of AD/HD (i.e., inattention and hyperactivity-impulsivity) in a sample of college students, utilizing a computerized attention task, the Attention Network Test (ANT). Different ANT task components have been found to activate separate brain areas linked to the functioning of alerting, orienting and executive attention, and have the potential to provide an indication of the efficiency of these brain networks. In addition to completing the ANT, the participants filled out questionnaires covering common symptoms of adult AD/HD, anxiety and depression. Hierarchical regression analyses revealed that there were no reliable relationships between self-reported symptoms of current inattention and hyperactivity-impulsivity and ANT performance. Further, self-reported depression and/or anxiety did not seem to impact the efficiency of attention networks to a significant degree in this study sample. Gender proved to be the most consistent predictor of ANT performance. Female gender was related to poorer executive attention efficiency. An exploratory ANCOVA revealed that individuals reporting high levels of impulsivity and emotional lability had poorer executive attention efficiency in comparison to those reporting these behaviors and problems to a lesser extent. Future research is needed in order to further explore the relationship between ANT performance and behavioral expressions of adult AD/HD and other neurological and psychiatric conditions.

Many processes and systems in nature and society can be characterized as large numbers of discrete elements that are (usually non-uniformly) interrelated. These networks were long thought to be random, but in the late 1990s, Barabási and Albert found that an underlying structure did in fact exist in many natural and technological networks that are now referred to as scale free. Since then, researchers have gained a much deeper understanding of this particular form of complexity, largely by combining graph theory, statistical physics, and advances in computing technology. This dissertation focuses on out-of-equilibrium dynamic processes as they unfold on these complex networks. Diffusion in networks of non-interacting nodes is shown to be temporally complex, while equilibrium is represented by a stable state with Poissonian fluctuations. Scale free networks achieve equilibrium very quickly compared to regular networks, and the most efficient are those with the lowest inverse power law exponent. Temporally complex diffusion also occurs in networks with interacting nodes under a cooperative decision-making model. At a critical value of the cooperation parameter, the most efficient scale free network achieves consensus almost as quickly as the equivalent all-to-all network. This finding suggests that the ubiquity of scale free networks in nature is due to Zipf's principle of least effort. It also suggests that an efficient scale free network structure may be optimal for real networks that require high connectivity but are hampered by high link costs.

This study explores the dynamics of network efficiency within business-to-business (B2B) relations in the Swedish recycling industry, by employing the concept of embeddedness and the interaction model. The complex network of connections between businesses play a crucial role in shaping their strategic decisions and sustainability outcomes, which are critical in today’s environmentally-conscious market. The aim of this study is then to investigate strategic decision-making within Sweden’s recycling sector, centering on the effect of network relations on firms’ strategies toward network efficiency. The research delves into the dual perspective of embeddedness - undersocialised and oversocialised views - to analyse how companies manage the equilibrium between economic objectives with the need for cooperative, value-driven interactions. Through conducting a qualitative study, using semi-structured interviews and secondary data, the research explores a case of a Swedish recycling firm with an extensive network. A framework was developed as a result of the findings, connecting the intricacies of embeddedness and interactions within B2B relations, and its impact on network efficiency and strategic decision-making. This study concludes that network efficiency among Swedish recycling firms in B2B relations is heavily influenced by embeddedness in their interactions. Thus, the findings emphasise the need for strategic actions that enhance relationship quality and fostering of mutual benefits. It highlights the importance of transparency, trust, and adaptability, recommending a balanced approach that incorporates both economic objectives and socio-environmental concerns. Firms can use this study’s findings as a guide for building and nurturing strong B2B network relations, and adapt it to their strategic actions regardless of the industry. Lastly, further research is encouraged to be conducted, using these factors, across diverse settings, suggesting their broader applicability beyond the recycling industry.

Submitted by Patrícia Cerveira (pcerveira1@gmail.com) on 2017-06-14T20:26:32Z No. of bitstreams: 1 Alex João.pdf: 2737215 bytes, checksum: 01f1f6dd1595e3849310212c302e540e (MD5) / Approved for entry into archive by Biblioteca da Escola de Engenharia (bee@ndc.uff.br) on 2017-06-29T15:57:07Z (GMT) No. of bitstreams: 1 Alex João.pdf: 2737215 bytes, checksum: 01f1f6dd1595e3849310212c302e540e (MD5) / Made available in DSpace on 2017-06-29T15:57:07Z (GMT). No. of bitstreams: 1 Alex João.pdf: 2737215 bytes, checksum: 01f1f6dd1595e3849310212c302e540e (MD5) / O advento do paradigma financeiras, ou outros tipos de limitações. Desta forma, redes com enlaces redundantes têm sua capacidade potencial desperdiçada pelo uso de protocolos de roteamento distribuídos que não conseguem lidar de forma adequada com todos os caminhos disponíveis. Em especial, as redes dos centros de dados que possuem um grande número de enlaces redundantes e têm que fornecer a comunicação de forma eficiente entre seus equipamentos. Nesta dissertação será apresentado o Equalize, um arcabouço criado segundo o paradigma RDS, que realiza o equilíbrio automático dos fluxos ingressantes na rede através dos enlaces disponíveis que estejam menos congestionados. A topologia da rede é "descoberta" de forma automática e a localização de um host é determinada pelo seu endereço de camada 2 (MAC), de forma que o mesmo pode migrar para qualquer ponto da rede mantendo seu endereço de camada 3 (IP) original. Para o cálculo do melhor caminho entre dois nós, o Equalize executa um algoritmo de Dijkstra adaptado, que emprega a utilização de cada enlace como parâmetro de custo. Assim, o Equalize estabelece na rede a funcionalidade de auto-balanceamento e também apresenta uma boa resiliência para falhas, além de suportar a migração de hosts (sejam eles físicos ou virtuais). Com essas características, Equalize é bastante adequado para redes com facilidade para um gerenciamento centralizado e com múltiplos caminhos entre seus equipamentos, como as redes dos centros de dados. Os resultados obtidos com a emulação de uma pequena rede mostram que a abordagem proposta é capaz de alcançar uma boa taxa de transferência na bissecção da rede, ao mesmo tempo em que garante o equilíbrio no uso dos enlaces contribuindo, assim, para o uso eficiente dos recursos de rede e melhorando a utilização de sua capacidade total disponível. / The advent of Software-Defined Networking (SDN) is promoting innovation and faster network development. Even though network design demands for robust, more capable and flexible approaches to cope with increasingly complexity, system eficiency is often limited due to resource bounding as a consequence of physical, technical, financial, or other types of constraints. Though, networks with multiple redundant links have their potential capacity wasted due to the use of distributed routing protocols that cannot adequately deal with all available paths. In particular, the data center networks that have a large number of redundant links and must provide eficient communications among edges. In this dissertation we present Equalize, a framework built upon the SDN paradigm, that automatically balances the network incoming flows among the less congested available links. The network topology is automatically "discovered" and the location of a host is determined by its layer 2 (MAC) address, so that it can migrate to any point in the network while keeping its original layer 3 (IP) address. To calculate the best path between two nodes, Equalize runs an adapted Dijkstra's algorithm, employing each link utilization as the cost parameter. Thus, Equalize establishes the self-balancing functionality in the network and also presents a good resilience to failures, besides supporting the migration of hosts (whether physical or virtual). Having those characteristics, Equalize is well suited for networks with ease of centralized management and multiple paths among edges, such as data center networks. The results obtained by emulating a small network show that the proposed approach is able to achieve a good bisection throughput, while enforcing the balance in the use of links, thereby contributing to eficient use of network resources and improving the utilization of its total capacity available.