Mapping the sensitivity of split ring resonators using a localized analyte

Split ring resonator (SRR) based metamaterials have frequently been demonstrated for use as optical sensors of organic materials. This is made possible by matching the wavelength of the SRR plasmonic resonance with a molecular resonance of a specific analyte, which is usually placed on top of the metal structure. However, systematic studies of SRRs that identify the regions that exhibit a high electric field strength are commonly performed using simulations. In this paper we demonstrate that areas of high electric field strength, termed “hot-spots,” can be found by localizing a small quantity of organic analyte at various positions on or near the structure. Furthermore, the sensitivity of the SRR to the localized analyte can be quantified to determine, experimentally, suitable regions for optical sensing

DIMENSIONAMENTO DOS SUPORTES EM ESCAVAÇÕES SUBTERRÂNEAS EM UMA MINA DE ZINCO

Resumo: O presente artigo tem como objetivo descrever os procedimentos, métodos para o dimensionamento de suportes em mina subterrânea e metodologias para avaliar a mecânica das rochas da mina em estudo. O dimensionamento desses suportes geralmente é baseado nas características da mina, no tipo de contenção com histórico de sucesso em outras minas e, mais recentemente, mesmo que só como referência, através de sistemas internacionais de classificação tais como Q de Barton e RMR de Bieniawski. Para o desenvolvimento dos trabalhos utilizou-se dados históricos provenientes da mina subterrânea de Vazante e coleta de dados realizados pela equipe de pesquisa. A escolha do suporte adequado deve sempre visar o melhor custo associado com produtividade e segurança mantendo a rocha estabilizada e reduzindo ou eliminando as probabilidades de ocorrência de colapsos. Palavras-chave: Dimensionamento, Suportes, sistemas internacionais de classificação

Indicadores financeiros da demonstração de fluxos de caixa : estudo da empresa Fibria Celulose S.A.

Orientador : Pedro Henrique Vilhena de Andrade Fonseca da SilvaMonografia (especialização) - Universidade Federal do Paraná, Setor de Ciências Sociais Aplicadas, Curso de Especialização em Gestão de NegóciosInclui referênciasResumo: Para avaliar o desempenho de uma empresa, devem ser analisados seus resultados e evoluções financeiras ao longo de sua história, além de seus resultados presentes. Para se fazer isso, pode-se analisar o balanço patrimonial e o Demonstrativo de Resultados do Exercício. A simples análise destes documentos, nem sempre transmite noções claras de desempenho, tanto para avaliações e decisões gerenciais, quanto, ou principalmente, para investidores, que, não necessáriamente conhecem detalhadamente contabilidade e finanças. Para expandir e facilitar o acesso a decisões de investimento, são recomendadas as análises de indicadores financeiros. Neste caso, optou-se aqui por focar nos indicadores de desempenho financeiro decorrentes da Demonstração dos Fluxos de Caixa e sugeridos por Braga e Marques (2001), os quais se baseiam principalmente no fluxo de caixa operacional. Este trabalho avalia o desempenho da empresa Fibria Celulose S.A. desde 2008, ano em que foi fortemente abalada pela crise financeira de abrangência mundial, até o ano de 2012, foi possível verificar o comportamento evolutório de indicadores, representando a recuperação da saúde financeira do grupo, possívelmente impulsionado pela elevada demanda mundial pelo produto, além das grandes oportunidades de reduções nos custos de produção proporcionadas pelas sinergias e elevada capacidade produtiva disponíveis após a fusão formadora da empresa, ocorrida no ano de 2009, entre Votorantim Celulose e Papel e Aracruz Celulose

A Soft Computing Approach to Acute Coronary Syndrome

Acute Coronary Syndrome (ACS) is transversal to a broad and heterogeneous set of human beings, and assumed as a serious diagnosis and risk stratification problem. Although one may be faced with or had at his disposition different tools as biomarkers for the diagnosis and prognosis of ACS, they have to be previously evaluated and validated in different scenarios and patient cohorts. Besides ensuring that a diagnosis is correct, attention should also be directed to ensure that therapies are either correctly or safely applied. Indeed, this work will focus on the development of a diagnosis decision support system in terms of its knowledge representation and reasoning mechanisms, given here in terms of a formal framework based on Logic Programming, complemented with a problem solving methodology to computing anchored on Artificial Neural Networks. On the one hand it caters for the evaluation of ACS predisposing risk and the respective Degree-of-Confidence that one has on such a happening. On the other hand it may be seen as a major development on the Multi-Value Logics to understand things and ones behavior. Undeniably, the proposed model allows for an improvement of the diagnosis process, classifying properly the patients that presented the pathology (sensitivity ranging from 89.7% to 90.9%) as well as classifying the absence of ACS (specificity ranging from 88.4% to 90.2%)

Innovation in retail banking: changing the university students perspective of banking

Banking related topics have always been out of interest for the Portuguese university students segment. This segment has very limited need for traditional bank offers and therefore has always been disconnected from the industry. Banks have been trying to reach the segment, by providing short-term benefits and marketing campaigns focused on creating new accounts. This approach has proved unfruitful, as students see the lack of customer-centered offers and do not identify with banking as a whole. Thus, they close their accounts shortly after they open them, roughly half closing the accounts before they are finished with higher education. Banks need to, therefore, change its image and offer on the university students’ segment in order to become more relevant. The aim of this Work Project is to design a long-term customer-centered product which is connected to the real needs of university students, while providing value to the Bank

A case-based reasoning view of thrombophilia risk

Thrombophilia stands for a genetic or an acquired tendency to hypercoagulable states that increase the risk of venous and arterial thromboses. Indeed, venous thromboembolism is often a chronic illness, mainly in deep venous thrombosis and pulmonary embolism, requiring lifelong prevention strategies. Therefore, it is crucial to identify the cause of the disease, the most appropriate treatment, the length of treatment or prevent a thrombotic recurrence. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a logic programming approach to knowledge representation and reasoning, complemented with a case-based approach to computing. The proposed model has been quite accurate in the assessment of thrombophilia predisposition risk, since the overall accuracy is higher than 90% and sensitivity ranging in the interval [86.5%, 88.1%]. The main strength of the proposed solution is the ability to deal explicitly with incomplete, unknown, or even self-contradictory information

An Integrated Soft Computing Approach to Hughes Syndrome Risk Assessment

The AntiPhospholipid Syndrome (APS) is an acquired autoimmune disorder induced by high levels of antiphospholipid antibodies that cause arterial and veins thrombosis, as well as pregnancy-related complications and morbidity, as clinical manifestations. This autoimmune hypercoagulable state, usually known as Hughes syndrome, has severe consequences for the patients, being one of the main causes of thrombotic disorders and death. Therefore, it is required to be preventive; being aware of how probable is to have that kind of syndrome. Despite the updated of antiphospholipid syndrome classification, the diagnosis remains difficult to establish. Additional research on clinically relevant antibodies and standardization of their quantification are required in order to improve the antiphospholipid syndrome risk assessment. Thus, this work will focus on the development of a diagnosis decision support system in terms of a formal agenda built on a Logic Programming approach to knowledge representation and reasoning, complemented with a computational framework based on Artificial Neural Networks. The proposed model allows for improving the diagnosis, classifying properly the patients that really presented this pathology (sensitivity higher than 85%), as well as classifying the absence of APS (specificity close to 95%)

A Case Base View of Heart Failure Predisposition Risk

Heart failure stands for an abnormality in cardiac structure or function which results in the incapability of the heart to deliver oxygen at an ideal rate. This is a worldwide problem of public health, characterized by high mortality, frequent hospitalization and reduced quality of life. Thus, this work will focus on the development of a decision support system to assess heart failure predisposing risk. The framework is built on top of a Logic Programming approach to Knowledge Representation and Reasoning, complemented with a Case Based approach to computing. The proposed solution is unique in itself, once it caters for the explicit treatment of incomplete, unknown, or even self-contradictory information, either in terms of a qualitative or quantitative setting. Furthermore, clustering methods based on similarity analysis among cases were used to distinguish and aggregate collections of historical data or knowledge in order to reduce the search space, therefore enhancing the cases retrieval and the overall computational process. The proposed model classifies properly the patients exhibiting accuracy and sensitivity higher than 90%

A soft computing approach to kidney diseases evaluation

Kidney renal failure means that one’s kidney have unexpectedly stopped functioning, i.e., once chronic disease is exposed, the presence or degree of kidney dysfunction and its progression must be assessed, and the underlying syndrome has to be diagnosed. Although the patient’s history and physical examination may denote good practice, some key information has to be obtained from valuation of the glomerular filtration rate, and the analysis of serum biomarkers. Indeed, chronic kidney sickness depicts anomalous kidney function and/or its makeup, i.e., there is evidence that treatment may avoid or delay its progression, either by reducing and prevent the development of some associated complications, namely hypertension, obesity, diabetes mellitus, and cardiovascular complications. Acute kidney injury appears abruptly, with a rapid deterioration of the renal function, but is often reversible if it is recognized early and treated promptly. In both situations, i.e., acute kidney injury and chronic kidney disease, an early intervention can significantly improve the prognosis.The assessment of these pathologies is therefore mandatory, although it is hard to do it with traditional methodologies and existing tools for problem solving. Hence, in this work, we will focus on the development of a hybrid decision support system, in terms of its knowledge representation and reasoning procedures based on Logic Programming, that will allow one to consider incomplete, unknown, and even contradictory information, complemented with an approach to computing centered on Artificial Neural Networks, in order to weigh the Degree-of-Confidence that one has on such a happening. The present study involved 558 patients with an age average of 51.7 years and the chronic kidney disease was observed in 175 cases. The dataset comprise twenty four variables, grouped into five main categories. The proposed model showed a good performance in the diagnosis of chronic kidney disease, since the sensitivity and the specificity exhibited values range between 93.1 and 94.9 and 91.9–94.2 %, respectively

Anterograde Removal of Broken Femoral Nails without Opening the Nonunion Site: A New Technique

OBJECTIVE: We describe a new technique for removing the distal fragments of broken intramedullary femoral nails without disturbing the nonunion site. METHODS: This technique involves the application of an AO distractor prior to the removal of the nail fragments, with subsequent removal of the proximal nail fragment in an anterograde fashion and removal of the distal fragment through a medial parapatellar approach. Impaction of the fracture site is then performed with a nail that is broader than the remaining fragmented material. RESULTS: Nails were removed from five patients using the technique described above without any complications. After a mean follow-up period of 61.8 months, none of these patients showed worsened knee osteoarthritis. CONCLUSION: The original technique described in this article allows surgeons to remove the distal fragment of fractured femoral intramedullary nails without opening the nonunion focus or using special surgical instruments