Plasmon polaritons in 1D Cantor-like fractal photonic superlattices containing a left-handed material

ABSTRACT: The propagation of light incident upon a 1D photonic superlattice consisting of successive stacking of alternate layers of a right-handed nondispersive material and a metamaterial, arranged to form a Cantor-like fractal, is considered. Plasmon-polariton excitations are thoroughly investigated within the transfer-matrix approach and shown to strongly depend on the Cantor step number N. More specifically, the number of plasmon-polariton bands corresponds to the number 2N −1 of metamaterial layers within the unit cell

The future of power systems: Challenges, trends, and upcoming paradigms

The decarbonization of the economy, for which the contribution of power systems is significant, is a growing trend in Europe and in the world. In order to achieve the Paris Agreement's ambitious environmental goals, a substantial increase in the contribution of renewable sources to the energy generation mix is required. This trend brings about relevant challenges as the integration of this type of sources increases, namely in terms of the distribution system operation. In this paper, the challenges foreseen for future power systems are identified and the most effective approaches to deal with them are reviewed. The strategies include the development of Smart Grid technologies (meters, sensors, and actuators) coupled with computational intelligence that act as new sources of data, as well as the connection of distributed energy resources to distribution grids, encompassing the deployment of distributed generation and storage systems and the dissemination of electric vehicles. The impact of these changes in the distribution system as a whole is evaluated from a technical and environmental perspective. In addition, a review of management and control architectures designed for distribution systems is conducted. This article is categorized under: Energy Infrastructure > Systems and Infrastructure Energy Infrastructure > Economics and Policy.ERDF - European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme, and by National Funds through the Portuguese funding agency, FCT - Fundacao para a Ciencia e a Tecnologia, Grant/Award Number: SAICTPAC/0004/2015-POCI-01-0145-FEDER-01643

Diversity and ethics in trauma and acute care surgery teams: results from an international survey

Background Investigating the context of trauma and acute care surgery, the article aims at understanding the factors that can enhance some ethical aspects, namely the importance of patient consent, the perceptiveness of the ethical role of the trauma leader, and the perceived importance of ethics as an educational subject. Methods The article employs an international questionnaire promoted by the World Society of Emergency Surgery. Results Through the analysis of 402 fully filled questionnaires by surgeons from 72 different countries, the three main ethical topics are investigated through the lens of gender, membership of an academic or non-academic institution, an official trauma team, and a diverse group. In general terms, results highlight greater attention paid by surgeons belonging to academic institutions, official trauma teams, and diverse groups. Conclusions Our results underline that some organizational factors (e.g., the fact that the team belongs to a university context or is more diverse) might lead to the development of a higher sensibility on ethical matters. Embracing cultural diversity forces trauma teams to deal with different mindsets. Organizations should, therefore, consider those elements in defining their organizational procedures. Level of evidence Trauma and acute care teams work under tremendous pressure and complex circumstances, with their members needing to make ethical decisions quickly. The international survey allowed to shed light on how team assembly decisions might represent an opportunity to coordinate team member actions and increase performance

Global validation of the WSES Sepsis Severity Score for patients with complicated intra-abdominal infections : a prospective multicentre study (WISS Study)

Background: To validate a new practical Sepsis Severity Score for patients with complicated intra-abdominal infections (cIAIs) including the clinical conditions at the admission (severe sepsis/septic shock), the origin of the cIAIs, the delay in source control, the setting of acquisition and any risk factors such as age and immunosuppression. Methods: The WISS study (WSES cIAIs Score Study) is a multicenter observational study underwent in 132 medical institutions worldwide during a four-month study period (October 2014-February 2015). Four thousand five hundred thirty-three patients with a mean age of 51.2 years (range 18-99) were enrolled in the WISS study. Results: Univariate analysis has shown that all factors that were previously included in the WSES Sepsis Severity Score were highly statistically significant between those who died and those who survived (p <0.0001). The multivariate logistic regression model was highly significant (p <0.0001, R-2 = 0.54) and showed that all these factors were independent in predicting mortality of sepsis. Receiver Operator Curve has shown that the WSES Severity Sepsis Score had an excellent prediction for mortality. A score above 5.5 was the best predictor of mortality having a sensitivity of 89.2 %, a specificity of 83.5 % and a positive likelihood ratio of 5.4. Conclusions: WSES Sepsis Severity Score for patients with complicated Intra-abdominal infections can be used on global level. It has shown high sensitivity, specificity, and likelihood ratio that may help us in making clinical decisions.Peer reviewe

Continuous improvement in thermal cutting activity

Relatório de Estágio do Mestrado Em Gestão apresentado à Faculdade de EconomiaAtualmente, as organizações enfrentam um cenário altamente competitivo com a crescente e constante globalização, o que as sujeita a encontrar formas de alcançar o máximo de eficiência na execução das suas operações e processos e, para tal, algumas estratégias devem ser equacionadas, nomeadamente, a Melhoria contínua nos seus processos produtivos. Esta por sua vez, relaciona-se com as filosofias Lean e Kaizen, que são filosofias que se debruçam na eliminação e redução de desperdícios. O presente relatório tem como finalidade demonstrar as atividades executadas durante o estágio curricular na empresa Inocambra- Construções Metálicas, S.A. que ocorreu durante o segundo semestre do ano letivo 2022/2023 e encontra-se estruturado em 4 partes. Numa primeira parte procura-se descrever o enquadramento do mesmo, ou seja, a apresentação da empresa e do estágio, incluído os objetivos e o planeamento. Numa segunda parte, encontra-se o enquadramento teórico sobre melhoria contínua e a filosofia kaizen, determinantes para a aplicação de melhorias no setor corte térmico. Seguidamente, explora-se as atividades desenvolvidas, com destaque para a abordagem às tecnologias, processos e produtos associados ao corte térmico e implementação de medidas que visam a eficiência da organização e dos seus serviços, enquadrados com o âmbito deste projeto. Na última etapa, efetua-se a análise critica das atividades desenvolvidas e dos respetivos resultados obtidos, em comparação com as perspetivas e objetivos previamente definidos.Considerando que todas as atividades desenvolvidas são resultado de implementações e/ou sugestões de melhoria aplicadas à empresa, este relatório realça a importância do espírito crítico na procura incessante pela melhoria da eficácia e eficiência em todas as áreas empresariais.A Melhoria Contínua em contexto de Processos de Corte Térmico é determinante para o cumprimento das exigências dos clientes e melhoria dos processos, em especial a comunicação, gestão de recursos, organização e melhoria de competências, com ênfase no aumento da rentabilidade e produtividade da entidade de acolhimento deste projeto.Currently, organizations face a highly competitive scenario with increasing and constant globalization, which subjects them to finding ways to achieve maximum efficiency in the execution of their operations and processes and, for this, some strategies must be equated, namely, the Continuous improvement in production processes. This, in turn, is related to the Lean and Kaizen philosophies, which are philosophies that focus on the elimination and reduction of waste.This report aims to demonstrate the activities carried out during the curricular internship at the company Inocambra- Construções Metálicas, S.A. which took place during the second semester of the academic year 2022/2023 and is structured in 4 parts. In the first part, an attempt is made to describe its framework, that is, the presentation of the company and the internship, including the objectives and planning. In a second part, there is the theoretical framework on continuous improvement and the kaizen philosophy, which are decisive for the application of improvements in the thermal cutting sector. Then, the activities carried out are explored, with emphasis on the approach to technologies, processes and products associated with thermal cutting and the implementation of measures aimed at the efficiency of the organization and its services, within the scope of this project. In the last stage, a critical analysis of the activities carried out and the respective results obtained is carried out, in comparison with the previously defined perspectives and objectives.Considering that all the activities carried out are the result of implementations and/or suggestions for improvement applied to the company, this report highlights the importance of a critical spirit in the relentless pursuit of improving effectiveness and efficiency in all business areas.Continuous Improvement in the context of Thermal Cutting Processes is crucial for meeting customer requirements and improving processes, in particular communication, resource management, organization and skills improvement, with an emphasis on increasing the profitability and productivity of the hosting this project

Towards Data Markets in Renewable Energy Forecasting

Geographically distributed wind turbines, photovoltaic panels and sensors (e.g., pyranometers) produce large volumes of data that can be used to improve renewable energy sources (RES) forecasting skill. However, data owners may be unwilling to share their data, even if privacy is ensured, due to a form of prisoner's dilemma: all could benefit from data sharing, but in practice no one is willing to do do. Our proposal hence consists of a data marketplace, to incentivize collaboration between different data owners through the monetization of data. We adapt here an existing auction mechanism to the case of RES forecasting data. It accommodates the temporal nature of the data, i.e., lagged time-series act as covariates and models are updated continuously using a sliding window. A test case with wind energy data is presented to illustrate and assess the effectiveness of such data markets. All agents (or data owners) are shown to benefit in terms of higher revenue resulting from the combination of electricity and data markets. The results support the idea that data markets can be a viable solution to promote data exchange between RES agents and contribute to reducing system imbalance costs

Treino On Line de Redes Neuronais com Critérios de Informação Aplicado à Previsão Eólica

Análise de Dados e Sistemas de Apoio à DecisãoMaster in Data Analysis and Decision Support SystemsNesta tese são estudadas redes neuronais MLP (Multilayer Perceptron) para previsão de produção eólica com treino on line para um horizonte temporal de 72 horas. O principal objectivo consiste em aplicar à previsão de produção eólica critérios de treino on line da rede neuronal, baseados na teoria da informação (ITL - Information Theoretic Learning). O principal motivo para a aplicação dos critérios ITL fundamenta-se no facto de a distribuição dos erros de previsão eólica não ser Gaussiana. Mesmo que as previsões de vento exibissem erros Gaussianos, a não linearidade da curva característica dos grupos eólicos produz erros não-Gaussianos, sendo as distribuições dos erros de previsão de potência eólica assimétricas positivas e mais achatadas que as Gaussianas. Quando se tratam distribuições de erros como se fossem Gaussianas desperdiça-se informação contida nos momentos de ordem superior. Quando se utiliza um critério de mínimos quadrados ou de variância (MSE) o processo de treino apenas passa uma parte da informação dos dados para os parâmetros do sistema, deixando na distribuição dos erros uma parte da informação. Com base no critério ITL foram estudados três critérios de treino da rede neuronal: minimização da entropia do erro (MEE), maximização da correntropia (MCC) e minimização da entropia do erro com pontos de referência (MEEF). Estes critérios de treino procuram conduzir a uma distribuição dos erros de previsão com entropia (informação) mínima, implicando maior frequência de erros próximos de zero. Os critérios combinam a definição de Renyi de Entropia com a técnica das janelas de Parzen, construindo uma medida do conteúdo de informação da distribuição dos erros. Tratando-se de um problema com um fluxo contínuo de dados não-estacionários foram desenvolvidas metodologias de treino on line da rede neuronal. O Treino on line permite incorporar nova informação proveniente do sistema de aquisição de dados do parque eólico, permitindo também processar um fluxo contínuo de dados sem necessidade de armazenar informação numa base de dados. Duas estratégias de treino on line foram desenvolvidas utilizando critérios de treino ITL: 1) retropropagação da correntropia do erro de um novo valor medido; 2) estimação recursiva da entropia do erro sobre uma janela temporal de tamanho pré-definido. Os testes dos diferentes critérios e modos de treino foram realizados sobre três parques eólicos situados em locais distintos de Portugal Continental e com diferente complexidade de terreno. Dos resultados obtidos foi possível apurar a superioridade da qualidade das previsões obtidas com os critérios ITL, quando comparadas com as obtidas com o MSE. O treino on line da rede neuronal quando comparado com o treino offline permitiu obter melhores previsões nos três parques e num caso especial em que ocorre uma mudança de conceito. Para o treino offline foi elaborada uma metodologia de estandardização dos parâmetros da rede de forma a tornar o treino da rede neuronal independente da complexidade do terreno e localização do parque eólico. No caso do treino on line é avaliado o impacto dos diferentes parâmetros no erro e exploradas algumas técnicas adaptativas dos parâmetros. Verificou-se que valores fixos dos parâmetros levavam a melhores resultados, no entanto, a utilização de abordagens adaptativas não deverá ser abandonada. As redes neuronais desenvolvidas nesta tese são uma ferramenta que se revela bastante importante e útil quando integrada em sistemas de previsão mais sofisticados

Privacy-preserving Distributed Learning for Renewable Energy Forecasting

Data exchange between multiple renewable energy power plant owners can lead to an improvement in forecast skill thanks to the spatio-temporal dependencies in time series data. However, owing to business competitive factors, these different owners might be unwilling to share their data. In order to tackle this privacy issue, this paper formulates a novel privacy-preserving framework that combines data transformation techniques with the alternating direction method of multipliers. This approach allows not only to estimate the model in a distributed fashion but also to protect data privacy, coefficients and covariance matrix. Besides, asynchronous communication between peers is addressed in the model fitting, and two different collaborative schemes are considered: centralized and peer-to-peer. The results for a solar energy dataset show that the proposed method is robust to privacy breaches and communication failures, and delivers a forecast skill comparable to a model without privacy protection