957 resultados para matched employer employee data


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O Grande panorama de Lisboa, obra maior da azulejaria nacional e hoje à guarda do Museu Nacional do Azulejo, pertenceu outrora a um palácio situado na freguesia de Santiago, propriedade da família Ferreira de Macedo no final do século XVII. A investigação apresentada procura esclarecer alguns aspectos relacionados com a execução do grandioso painel e com o perfil sócio-cultural do encomendador. À luz de novos elementos documentais, o artigo discute ainda a questão da autoria do painel, dada há muito ao pintor barroco Gabriel del Barco.

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O transporte marítimo tem vindo a adquirir uma considerável importância na economia mundial desde o século XV. O transporte marítimo é visto como um dos meios de transporte mais viáveis, que engloba um largo número de destinos no mundo e representa, para uma determinada distância a percorrer, o menor custo por tonelada. É, também, comparativamente com o transporte aéreo e rodoviário, o meio de transporte menos poluente, tornando-o, assim, uma alternativa “amiga do ambiente”. Em particular, o transporte via contentores tem vindo a ser cada vez mais utilizado devido às suas inúmeras vantagens. O contentor permite o transporte de qualquer tipo de mercadoria em boas condições de acondicionamento e permitiu otimizar as operações efetuadas através da redução de tempo de trabalho, custos e espaço. Ademais, com a globalização, a evolução do mercado, a construção de navios de maiores dimensões e a maior tecnologia investida no setor, a competição entre os portos alcançou níveis que exigem uma maior eficiência de toda a estrutura portuária. Neste contexto, a presente dissertação visa avaliar a eficiência dos terminais de contentores do grupo TERTIR, nomeadamente os de Lisboa, Leixões e Setúbal, utilizando o método Data Envelopment Analaysis (DEA). De um modo geral, o método DEA avalia a capacidade dos terminais em converter inputs em outputs. Mais especificamente os inputs selecionados nesta dissertação dizem respeito às infraestruturas e equipamentos dos terminais em estudo, e o output considera a carga movimentada por cada terminal, sendo neste caso representada pelo número de TEUs movimentados. O modelo proposto é aplicado a um conjunto de 30 terminais de contentores Europeus de 6 países diferentes, nomeadamente, Alemanha, Bélgica, Espanha, França, Holanda e Portugal. De um modo geral, os terminais TERTIR apresentam níveis de eficiência baixos quando comparados com outros terminais Europeus. Os resultados contribuem, também, para auxiliar o grupo TERTIR no debate de algumas questões atuais com as autoridades portuárias, nomeadamente no que se refere à descida dos tarifários praticados aos seus clientes e à enunciada construção do terminal de contentores do Barreiro.

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This work is devoted to the broadband wireless transmission techniques, which are serious candidates to be implemented in future broadband wireless and cellular systems, aiming at providing high and reliable data transmission and concomitantly high mobility. In order to cope with doubly-selective channels, receiver structures based on OFDM and SC-FDE block transmission techniques, are proposed, which allow cost-effective implementations, using FFT-based signal processing. The first subject to be addressed is the impact of the number of multipath components, and the diversity order, on the asymptotic performance of OFDM and SC-FDE, in uncoded and for different channel coding schemes. The obtained results show that the number of relevant separable multipath components is a key element that influences the performance of OFDM and SC-FDE schemes. Then, the improved estimation and detection performance of OFDM-based broadcasting systems, is introduced employing SFN (Single Frequency Network) operation. An initial coarse channel is obtained with resort to low-power training sequences estimation, and an iterative receiver with joint detection and channel estimation is presented. The achieved results have shown very good performance, close to that with perfect channel estimation. The next topic is related to SFN systems, devoting special attention to time-distortion effects inherent to these networks. Typically, the SFN broadcast wireless systems employ OFDM schemes to cope with severely time-dispersive channels. However, frequency errors, due to CFO, compromises the orthogonality between subcarriers. As an alternative approach, the possibility of using SC-FDE schemes (characterized by reduced envelope fluctuations and higher robustness to carrier frequency errors) is evaluated, and a technique, employing joint CFO estimation and compensation over the severe time-distortion effects, is proposed. Finally, broadband mobile wireless systems, in which the relative motion between the transmitter and receiver induces Doppler shift which is different or each propagation path, is considered, depending on the angle of incidence of that path in relation to the direction of travel. This represents a severe impairment in wireless digital communications systems, since that multipath propagation combined with the Doppler effects, lead to drastic and unpredictable fluctuations of the envelope of the received signal, severely affecting the detection performance. The channel variations due this effect are very difficult to estimate and compensate. In this work we propose a set of SC-FDE iterative receivers implementing efficient estimation and tracking techniques. The performance results show that the proposed receivers have very good performance, even in the presence of significant Doppler spread between the different groups of multipath components.

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Purpose – The purpose of this paper is to explore the impact of corporate volunteering on employee bonding and to understand the barriers and motivation to participation in these events. In contrast to other studies the participants volunteer in their spare time without expecting any financial reward. Design/methodology/approach – Employees (n 3951) of a logistic company participated in the study based on an online questionnaire with 6 items and open questions. The employee sample was divided into 3 groups depending on the frequency of participation in volunteering events. Findings – Significant differences were found on bonding between the three groups. In addition, the relevance of control variables like gender, age and job level were obtained. Furthermore a moderation effect of motivation was found. The results were interpreted within the broader context that ties motivation theory, organizational identification and social exchange theory.

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RESUMO: Actualmente, a única possibilidade de cura para doentes com adenocarcinoma do pâncreas (PDAC) é a ressecção cirúrgica, no início deste estudo, perguntamo-nos se os predictores clínico-patológicos clássicos de prognostico poderiam ser validados em uma grande cohort de doentes com cancro do pâncreas ressecável e se outros predictores clínicos poderiam ter um papel na decisão de que doentes beneficiariam de ressecção cirúrgica. No capítulo 2, observamos que até 30% dos doentes morrem no primeiro ano após a ressecção cirúrgica, pelo que o nosso objectivo foi determinar factores pré-operatórios que se correlacionam com mortalidade precoce após ressecação cirúrgica com recurso a um instrumento estatisticamente validado, o Charlson-Age Comorbidity Index (CACI), determinamos que um CACI score superior a 4 foi preditivo de internamentos prolongados (p <0,001), complicações pós-operatórias (p = 0,042), e mortalidade em 1 ano pós- ressecção cirúrgica (p <0,001). Um CACI superior a 6 triplicou a mortalidade no primeiro ano pós-cirurgia e estes doentes têm menos de 50% de probabilidade de estarem vivos um ano após a cirurgia. No capítulo 3, o nosso objectivo foi identificar uma proteína de superfície que se correlacionasse estatisticamente com o prognostico de doentes com adenocarcinoma do pâncreas e permitisse a distinção de subgrupos de doentes de acordo com as suas diferenças moleculares, perguntamo-nos ainda se essa proteína poderia ser um marcador de células-estaminais. No nosso trabalho anterior observamos que as células tumorais na circulação sanguínea apresentavam genes com características bifenotípica epitelial e mesenquimal, enriquecimento para genes de células estaminais (ALDH1A1 / ALDH1A2 e KLF4), e uma super-expressão de genes da matriz extracelular (colagénios, SPARC, e DCN) normalmente identificados no estroma de PDAC. Após a avaliação dos tumores primários com RNA-ISH, muitos dos genes identificados, foram encontrados co-localizando em uma sub-população de células na região basal dos ductos pancreáticos malignos. Além disso, observamos que estas células expressam o marcador SV2A neuroendócrino, e o marcador de células estaminais ALDH1A1/2. Em comparação com tumores negativos para SV2, os doentes com tumores SV2 positivos apresentaram níveis mais baixos de CA 19-9 (69% vs. 52%, p = 0,012), tumores maiores (> 4 cm, 23% vs. 10%, p = 0,0430), menor invasão de gânglios linfáticos (69% vs. 86%, p = 0,005) e tumores mais diferenciados (69% vs. 57%, p = 0,047). A presença de SV2A foi associada com uma sobrevida livre de doença mais longa (HR: 0,49 p = 0,009) bem como melhor sobrevida global (HR: 0,54 p = 0,018). Em conjunto, esta informação aponta para dois subtipos diferentes de adenocarcinoma do pâncreas, e estes subtipos co-relacionam estatisticamente com o prognostico de doentes, sendo este subgrupo definido pela presença do clone celular SV2A / ALDH1A1/2 positivo com características neuroendócrinas. No Capítulo 4, a expressão de SV2A no cancro do pâncreas foi validado em linhas celulares primárias. Demonstramos a heterogeneidade do adenocarcinoma do pâncreas de acordo com características clonais neuroendócrinas. Ao comparar as linhas celulares expressando SV2 com linhas celulares negativas, verificamos que as linhas celulares SV2+ eram mais diferenciadas, diferindo de linhas celulares SV2 negativas no que respeita a mutação KRAS, proliferação e a resposta à quimioterapia. No capítulo 5, perguntamo-nos se o clone celular SV2 positivo poderia explicar a resistência a quimioterapia observada em doentes. Observamos um aumento absoluto de clones celulares expressando SV2A, em múltiplas linhas de evidência - doentes, linhas de células primárias e xenotransplantes. Embora, tenhamos sido capazes de demonstrar que o adenocarcinoma do pâncreas é uma doença heterogénea, consideramos que a caracterização genética destes clones celulares expressando SV2A é de elevada importância. Pretendemos colmatar esta limitação com as seguintes estratégias: Após o tratamento com quimioterapia neoadjuvante na nossa coorte, realizamos microdissecação a laser das amostras primarias em parafina, de forma a analisar mutações genéticas observadas no adenocarcinoma pancreático; em segundo lugar, pretendemos determinar consequências de knockdown da expressão de SV2A em nossas linhas celulares seguindo-se o tratamento com gemicitabina para determinação do papel funcional de SV2A; finalmente, uma vez que os nossos esforços anteriores com um promotor - repórter e SmartFlare ™ falharam, o próximo passo será realizar RNA-ISH PrimeFlow™ seguido de FACS e RNA-seq para caracterização deste clone celular. Em conjunto, conseguimos provar com várias linhas de evidência, que o adenocarcinoma pancreático é uma doença heterogénea, definido por um clone de células que expressam SV2A, com características neuroendócrinas. A presença deste clone no tecido de doentes correlaciona-se estatisticamente com o prognostico da doença, incluindo sobrevida livre de doença e sobrevida global. Juntamente com padrões de proliferação e co-expressão de ALDH1A1/2, este clone parece apresentar um comportamento de células estaminais e está associado a resistência a quimioterapia, uma vez que a sua expressão aumenta após agressão química, quer em doentes, quer em linhas de células primárias.----------------------------- ABSTRACT: Currently, the only chance of cure for patients with pancreatic adenocarcinoma is surgical resection, at the beginning of my thesis studies, we asked if the classical clinicopathologic predictors of outcome could be validated in a large cohort of patients with early stage pancreatic cancer and if other clinical predictors could have a role on deciding which patients would benefit from surgery. In chapter 2, we found that up to 30% of patients die within the first year after curative intent surgery for pancreatic adenocarcinoma. We aimed at determining pre-operative factors that would correlate with early mortality following resection for pancreatic cancer using a statistically validated tool, the Charlson-Age Comorbidity Index (CACI). We found that a CACI score greater than 4 was predictive of increased length of stay (p<0.001), post-operative complications (p=0.042), and mortality within 1-year of pancreatic resection (p<0.001). A CACI score of 6 or greater increased 3-fold the odds of death within the first year. Patients with a high CACI score have less than 50% likelihood of being alive 1 year after surgery. In chapter 3 we aimed at identifying a surface protein that correlates with patient’s outcome and distinguishes sub-groups of patients according to their molecular differences and if this protein could be a cancer stem cell marker. The most abundant class of circulating tumor cells identified in our previous work was found to have biphenotypic features of epithelial to mesenchymal transition, enrichment for stem-cell associated genes (ALDH1A1/ALDH1A2 and KLF4), and an overexpression of extracellular matrix genes (Collagens, SPARC, and DCN) normally found in the stromal microenvironment of PDAC primary tumors. Upon evaluation of matched primary tumors with RNA-ISH, many of the genes identified were found to co-localize in a sub-population of cells at the basal region of malignant pancreatic ducts. In addition, these cells expressed the neuroendocrine marker SV2A, and the stem cell marker ALDH1A1/2. Compared to SV2 negative tumors, patients with SV2 positive tumors were more likely to present with lower CA 19-9 (69% vs. 52%, p = 0.012), bigger tumors (size > 4 cm, 23% vs. 10%, p= 0.0430), less nodal involvement (69% vs. 86%, p = 0.005) and lower histologic grade (69% vs. 57%, p = 0.047). The presence of SV2A expressing cells was associated with an improved disease free survival (HR: 0.49 p=0.009) and overall survival (HR: 0.54 p=0.018) and correlated linearly with ALDH1A2. Together, this information points to two different sub-types of pancreatic adenocarcinoma, and these sub-types correlated with patients’ outcome and were defined by the presence of a SV2A/ ALDH1A1/2 expressing clone with neuroendocrine features. In Chapter 4, SV2A expression in cancer was validated in primary cell lines. We were able to demonstrate pancreatic adenocarcinoma heterogeneity according to neuroendocrine clonal features. When comparing SV2 expressing cell lines with SV2 negative cell lines, we found that SV2+ cell lines were more differentiated and differ from SV2 negative cell lines regarding KRAS mutation, proliferation and response to chemotherapy. In Chapter 5 we aimed at determining if this SV2 positive clone could explain chemoresistance observed in patients. We found an absolute increase in SV2A expressing cells, with multiple lines of evidence, in patients, primary cell lines and xenografts. Although, we have been able to show evidence that pancreatic adenocarcinoma is a heterogeneous disease, our findings warrant further investigation. To further characterize SV2A expressing clones after treatment with neoadjuvant chemotherapy in our cohort, we have performed laser capture microdissection of the paraffin embedded tissue in this study and will analyze the tissue for known genetic mutations in pancreatic adenocarcinoma; secondly, we want to know what will happen after knocking down SV2A expression in our cell lines followed by treatment with gemcitabine to determine if SV2A is functionally important; finally, since our previous efforts with a promoter – reporter and SmartFlare™ have failed, we will utilize a novel PrimeFlow™ RNA-ISH assay followed by FACS and RNA sequencing to further characterize this cellular clone. Overall our data proves, with multiple lines of evidence, that pancreatic adenocarcinoma is a heterogeneous disease, defined by a clone of SV2A expressing cells, with neuroendocrine features. The presence of this clone in patients’ tissue correlates with patient’s disease free survival and overall survival. Together with patterns of proliferation and ALDH1A1/2 co-expression, this clone seems to present a stem-cell-like behavior and is associated with chemoresistance, since it increases after chemotherapy, both in patients and primary cell lines.

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Ship tracking systems allow Maritime Organizations that are concerned with the Safety at Sea to obtain information on the current location and route of merchant vessels. Thanks to Space technology in recent years the geographical coverage of the ship tracking platforms has increased significantly, from radar based near-shore traffic monitoring towards a worldwide picture of the maritime traffic situation. The long-range tracking systems currently in operations allow the storage of ship position data over many years: a valuable source of knowledge about the shipping routes between different ocean regions. The outcome of this Master project is a software prototype for the estimation of the most operated shipping route between any two geographical locations. The analysis is based on the historical ship positions acquired with long-range tracking systems. The proposed approach makes use of a Genetic Algorithm applied on a training set of relevant ship positions extracted from the long-term storage tracking database of the European Maritime Safety Agency (EMSA). The analysis of some representative shipping routes is presented and the quality of the results and their operational applications are assessed by a Maritime Safety expert.

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A Internet das Coisas tal como o Big Data e a análise dos dados são dos temas mais discutidos ao querermos observar ou prever as tendências do mercado para as próximas décadas, como o volume económico, financeiro e social, pelo que será relevante perceber a importância destes temas na atualidade. Nesta dissertação será descrita a origem da Internet das Coisas, a sua definição (por vezes confundida com o termo Machine to Machine, redes interligadas de máquinas controladas e monitorizadas remotamente e que possibilitam a troca de dados (Bahga e Madisetti 2014)), o seu ecossistema que envolve a tecnologia, software, dispositivos, aplicações, a infra-estrutura envolvente, e ainda os aspetos relacionados com a segurança, privacidade e modelos de negócios da Internet das Coisas. Pretende-se igualmente explicar cada um dos “Vs” associados ao Big Data: Velocidade, Volume, Variedade e Veracidade, a importância da Business Inteligence e do Data Mining, destacando-se algumas técnicas utilizadas de modo a transformar o volume dos dados em conhecimento para as empresas. Um dos objetivos deste trabalho é a análise das áreas de IoT, modelos de negócio e as implicações do Big Data e da análise de dados como elementos chave para a dinamização do negócio de uma empresa nesta área. O mercado da Internet of Things tem vindo a ganhar dimensão, fruto da Internet e da tecnologia. Devido à importância destes dois recursos e á falta de estudos em Portugal neste campo, com esta dissertação, sustentada na metodologia do “Estudo do Caso”, pretende-se dar a conhecer a experiência portuguesa no mercado da Internet das Coisas. Visa-se assim perceber quais os mecanismos utilizados para trabalhar os dados, a metodologia, sua importância, que consequências trazem para o modelo de negócio e quais as decisões tomadas com base nesses mesmos dados. Este estudo tem ainda como objetivo incentivar empresas portuguesas que estejam neste mercado ou que nele pretendam aceder, a adoptarem estratégias, mecanismos e ferramentas concretas no que diz respeito ao Big Data e análise dos dados.

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Qualquer assunto relacionado com a saúde é sempre um tema sensível, pela importância que tem junto da população, já que interage diretamente com o bem-estar das pessoas e, essencialmente, com a sensação de segurança que as estas pretendem ter na prestação dos cuidados básicos de saúde. Dados estatísticos mostram que a população está cada vez mais envelhecida, reforçando a importância da existência de bons centros hospitalares e de um bom Sistema Nacional de Saúde (SNS) (Plano Nacional de Saúde, 2010). Em Portugal, caso os pacientes necessitem de cuidados mais urgentes, podem recorrer ao Serviço de Urgências disponibilizado para toda a população através do SNS. No entanto, a gestão e planeamento deste serviço é complexa, dado este serviço ser frequentemente utilizado por pacientes que não necessitam de cuidados urgentes, levando a que os hospitais deixem de conseguir dar a resposta esperada, implicando a prestação por vezes um serviço de menor qualidade. Neste sentido, analisaram-se dados de um hospital do norte do país com o intuito de perceber o ponto de situação das urgências, de forma a encontrar padrões relevantes através da análise de clusters e de regras de associação. Começando pela análise de clusters, utilizaram-se apenas as variáveis que foram consideradas importantes para o problema, resultando da análise final 3 clusters. O primeiro cluster é constituído por elementos do sexo masculino de todas as idades, o segundo cluster por elementos do sexo masculino mais jovens e por elementos do sexo feminino até aos 60 anos e o terceiro cluster apenas por elementos do sexo feminino a partir dos 40 anos. No final verificaram-se muitas semelhanças entre os clusters 1 e 3, pois ambos continham os pacientes mais idosos, havendo um padrão comum no seu comportamento. No ano 2012 não houve registo de nenhuma epidemia, não havendo por isso nenhuma doença que se destacasse comparativamente às restantes. Concluiu-se também que na maior parte dos casos houve a necessidade de uma intervenção urgente (pulseira de cor Amarela), no entanto a maioria dos pacientes observados conseguiu regressar às suas habitações após as consultas nas Urgências Hospitalares, sem intervenções médicas adicionais. Relativamente às regras de associação, houve a necessidade de transformar e eliminar algumas variáveis que enviesassem o estudo. Após o processo da criação das regras de associação, percebeu-se que as regras eram muito similares entre si, apresentando uma maior confiança nas variáveis que apareceram em maior número (“Pacientes com pulseira de cor Amarela”, “distrito do Porto” ou “Alta Médica para a Residência”).

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This paper sets out to determine how small accounting firms can compete in the United States in the early 21st century. The first chapter identifies the central goal of the paper: namely, to use existing literature and market data to define a business strategy for Ross & Moncure, Inc., a small accounting firm in the metropolitan Washington area. The second chapter is a literature review, and in it the author finds that large accounting firms are advantaged in terms of reputation, ability to diversify, and ability to retain employees, but are disadvantaged in their ability to form longstanding successful relationships with clients. In the third chapter, the author explores the relationship between the Big Four firms and their employees. The goal of this chapter is to determine how small accounting firms can compete for top talent in the HR market, and the author finds that this can be done by offering faster career progression and more client interaction. The fourth chapter looks at the market for accounting services in the United States, exploring the different options that consumers have to meet their accounting needs. It is found in this chapter that big and small accounting firms tend to compete for clients of different profiles. In the fifth chapter, the author uses proprietary company data to explore the composition, existing strategy and culture of Ross & Moncure. In the sixth chapter, all of the previous chapters come together to formulate a strategy and plan for action for Ross & Moncure: specifically, that the firm should further cultivate networks and relationships, and should create a fulfilling professional environment by increasing client-employee interaction, encouraging external education, and allowing employees to take on many different projects

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The interest in using information to improve the quality of living in large urban areas and its governance efficiency has been around for decades. Nevertheless, the improvements in Information and Communications Technology has sparked a new dynamic in academic research, usually under the umbrella term of Smart Cities. This concept of Smart City can probably be translated, in a simplified version, into cities that are lived, managed and developed in an information-saturated environment. While it makes perfect sense and we can easily foresee the benefits of such a concept, presently there are still several significant challenges that need to be tackled before we can materialize this vision. In this work we aim at providing a small contribution in this direction, which maximizes the relevancy of the available information resources. One of the most detailed and geographically relevant information resource available, for the study of cities, is the census, more specifically the data available at block level (Subsecção Estatística). In this work, we use Self-Organizing Maps (SOM) and the variant Geo-SOM to explore the block level data from the Portuguese census of Lisbon city, for the years of 2001 and 2011. We focus on gauging change, proposing ways that allow the comparison of the two time periods, which have two different underlying geographical bases. We proceed with the analysis of the data using different SOM variants, aiming at producing a two-fold portrait: one, of the evolution of Lisbon during the first decade of the XXI century, another, of how the census dataset and SOM’s can be used to produce an informational framework for the study of cities.

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Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

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As huge amounts of data become available in organizations and society, specific data analytics skills and techniques are needed to explore this data and extract from it useful patterns, tendencies, models or other useful knowledge, which could be used to support the decision-making process, to define new strategies or to understand what is happening in a specific field. Only with a deep understanding of a phenomenon it is possible to fight it. In this paper, a data-driven analytics approach is used for the analysis of the increasing incidence of fatalities by pneumonia in the Portuguese population, characterizing the disease and its incidence in terms of fatalities, knowledge that can be used to define appropriate strategies that can aim to reduce this phenomenon, which has increased more than 65% in a decade.

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This paper presents a methodology based on the Bayesian data fusion techniques applied to non-destructive and destructive tests for the structural assessment of historical constructions. The aim of the methodology is to reduce the uncertainties of the parameter estimation. The Young's modulus of granite stones was chosen as an example for the present paper. The methodology considers several levels of uncertainty since the parameters of interest are considered random variables with random moments. A new concept of Trust Factor was introduced to affect the uncertainty related to each test results, translated by their standard deviation, depending on the higher or lower reliability of each test to predict a certain parameter.

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Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.

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Immature and adult stages of Anopheles (Anopheles) forattinii were collected in the Parque Nacional do Jaú, Novo Airão, Amazonas, Brazil. Larvae and pupae were taken from fresh water among floating plant debris inside flooded "igapó" forest. This species may make use of plant debris for passive dispersal throughout its distribution range.