On the classification problem for split graphs

Abstract The Classification Problem is the problem of deciding whether a simple graph has chromatic index equal to Δ or Δ+1. In the first case, the graphs are called Class 1, otherwise, they are Class 2. A split graph is a graph whose vertex set admits a partition into a stable set and a clique. Split graphs are a subclass of chordal graphs. Figueiredo at al. (J. Combin. Math. Combin. Comput. 32:79–91, 2000) state that a chordal graph is Class 2 if and only if it is neighborhood-overfull. In this paper, we give a characterization of neighborhood-overfull split graphs and we show that the above conjecture is true for some split graphs

CHEMICAL COMPOSITION, ANTIOXIDANT AND ANTIMICROBIAL PROPERTIES OF THREE ESSENTIAL OILS FROM PORTUGUESE FLORA

The present work reports on the evaluation of chemical composition and antioxidant and antimicrobial activities of essential oils of three aromatic herbs, growing wild in the south of Portugal, used in traditional food preparations: Foeniculum vulgare, Mentha spicata and Rosmarinus officinalis. The principal components of essential oils were anethole (41.2%) for F. vulgare, carvone (41.1%) for M. spicata and myrcene (23.7%) for R. officinalis. Essential oils showed antioxidant activity either by DPPH radical scavenging method and system β- carotene/acid linoleic method. Antimicrobial activity of essential oils was observed against pathogenic bacteria and yeasts and food spoilage fungi. F.vulgare essential oil showed bacterial activity against Escherichia coli, Klebsiella pneumoniae, Proteus mirabilis, Pseudomonas aeruginosa, Salmonella enteritidis, Staphylococcus aureus, Aspergillus niger and Fusarium oxysporum with MICs of 0.25-0.75mg/mL. M. spicata oil was active against E.coli, S.aureus, C.albicans, A. niger and F. oxysporum with MICs ranging between 0.25 and 0.75mg/mL. R. officinalis essential oil showed activity against E.coli and C.albicans with MICs of 0.5-1.0mg/mL. Having in account the important antioxidant and antimicrobial properties observed in present work, we consider that these essential oils might be useful on pharmaceutical and food industry as natural antibiotic and food preservativ

Off-label prescribing for allergic diseases in pre-school children

BACKGROUND: Several studies have demonstrated that medication is commonly used off-label in children with allergic diseases. The aim of this study was to characterise off-label use of prescriptions for allergic diseases in pre-school children from an allergology outpatient unit. METHODS: The clinical files of children aged ≤6 years seen in a reference allergology consultation with asthma, allergic rhinitis, and/or atopic eczema were reviewed. A total of 500 patients were consecutively observed from January to June 2012. The data collected included gender, age, diagnosis, and prescriptions with the respective daily dosage. RESULTS: A total of 1224 prescriptions were registered. The most prescribed medications were oral antihistamines (34.6%), antileukotrienes (22.6%), topical nasal corticosteroids (20.3%), and inhaled corticosteroids (17.7%). From all prescriptions, 422 (34.5%) were considered off-label for age (62.6%), dosage (31.7%), or clinical indication (5.7%). Off-label use was more frequent in children aged <2 years, with 73.5% prescribed for children of this age. CONCLUSIONS: Off-label use of drugs for the treatment of paediatric allergic diseases is high. However, these prescriptions are not necessarily wrong, and are recommended in many guidelines. Randomised controlled studies are limited by methodological difficulties creating the need for more observational studies in order to further evaluate the safety and efficacy of drugs used in children

Kounis Syndrome Associated With Selective Anaphylaxis to Cefazolin.

info:eu-repo/semantics/publishedVersio

Épidémiologie de l’Asthme dans les Pays Lusophones

Asthma in schoolchildren became a priority both for developing and developed countries. Two large multi-centre epidemiological studies(Portuguese Study of Allergic Diseases in Childhood and the International Study of Asthma and Allergies in Childhood) were implemented in the last decade. One of the main objectives was to compare prevalence of asthma and evaluate cultural, ethnic and environmental variables in schoolchildren of different continents. These studies can contribute to a global strategy (with national specificity’s) including self management programs in the control of asthma to reduce the morbidity and mortality, and promote better quality of life with better allocation of resources

Relatório de Estágio no Serviço de Cuidados Intensivos I do Centro Hospitalar do Porto

Berry Maurice. Reconstitution du tympan de l'église Saint-Yves de Braine. In: Bulletin de la Société Nationale des Antiquaires de France, 1971, 1973. pp. 235-243

Upgrading decision support systems with Cloud-based environments and machine learning

Business Intelligence (BI) is a process for analyzing raw data and displaying it in order to make it easier for business users to take the right decision at the right time. Inthe market we can find several BI platforms. One commonly used BI solution is calledMicroStrategy, which allows users to build and display reports.Machine Learning (ML) is a process of using algorithms to search for patterns in data which are used to predict and/or classify other data.In recent years, these two fields have been integrated into one another in order to try to complement the prediction side of BI to enable higher quality results for the client.The consulting company (CC) where I have worked on has several solutions related to Data & Analytics built on top of Micro Strategy. Those solutions were all demonstrable in a server installed on-premises. This server was also utilized to build proofs of concept(PoC) to be used as demos for other potential clients. CC also develops new PoCs for clients from the ground up, with the objective of show casing what is possible to display to the client in order to optimize business management.CC was using a local, out of date server to demo the PoCs to clients, which suffered from stability and reliability issues. To address these issues, the server has been migrated and set up in a cloud based solution using a Microsoft Azure-based Virtual Machine,where it now performs similar functions compared to its previous iteration. This move has made the server more reliable, as well as made developing new solutions easier forthe team and enabled a new kind of service (Analytics as a Service).My work at CC was focused on one main task: Migration of the demo server for CCsolutions (which included PoCs for testing purposes, one of which is a machine learning model to predict wind turbine failures). The migration was successful as previously stated and the prediction models, albeit with mostly negative results, demonstrated successfully the development of large PoCs.Business Intelligence (BI) é um processo para analizar dados não tratados e mostrá-los para ajudar gestores a fazer a decisão correcta no momento certo. No mercado, pode-se encontrar várias plataformas de BI. Uma solução de BI comum chama-se MicroStrategy,que permite com que os utilizadores construam e mostrem relatórios.Machine Learning (ML) é um processo de usar algoritmos para procurar padrões em dados que por sua vez são usados para prever e/ou classificar outros dados.Nos últimos anos, estes campos foram integrados um no outro para tentar complementar o lado predictivo de BI para possibilitar resultados de mais alta qualidade para o cliente.A empresa de consultoria (EC) onde trabalhei tem várias soluções relacionadas com Data e Analytics construídas com base no MicroStrategy. Essas soluções eram todas demonstráveis num servidor instalado no local. Este servidor também era usado para criar provas de conceito (PoC) para serem usadas como demos para outros potenciais clientes.A EC também desenvolve novas PoCs para clientes a partir do zero, com o objectivo de demonstrar ao cliente o que é possível mostrar para optimizar a gestão do negócio.A EC estava a utilizar um servidor local desactualizado para demonstrar os PoCs aos clientes, que tinha problemas de estabilidade e fiabilidade. Para resolver estes problemas,o servidor foi migrado e configurado numa solução baseada na cloud com o uso de uma Máquina Virtual baseada no Microsoft Azure, onde executa funções semelhantes à versão anterior. Esta migração tornou o servidor mais fiável, simplificou o processo de desenvolver novas soluções para a equipa e disponibilizou um novo tipo de serviço (Analytics as a Service).O meu trabalho na EC foi focado numa tarefas principal: Migração do servidor de demonstrações de soluções CC (que inclui PoCs para propósitos de testes, uma das quais é um modelo de aprendizagem de máquina para prever falhas em turbinas eólicas). A migração foi efectuada com sucesso (como mencionado previamente) e os modelos testados,apesar de terem maioritariamente resultados negativos, demonstraram com sucesso que é possível desenvolver PoCs de grande dimensão