Scalable allocation of safety integrity levels in automotive systems

The allocation of safety integrity requirements is an important problem in modern safety engineering. It is necessary to find an allocation that meets system level safety integrity targets and that is simultaneously cost-effective. As safety-critical systems grow in size and complexity, the problem becomes too difficult to be solved in the context of a manual process. Although this thesis addresses the generic problem of safety integrity requirements allocation, the automotive industry is taken as an application example.Recently, the problem has been partially addressed with the use of model-based safety analysis techniques and exact optimisation methods. However, usually, allocation cost impacts are either not directly taken into account or simple, linear cost models are considered; furthermore, given the combinatorial nature of the problem, applicability of the exact techniques to large problems is not a given. This thesis argues that it is possible to effectively and relatively efficiently solve the allocation problem using a mixture of model-based safety analysis and metaheuristic optimisation techniques. Since suitable model-based safety analysis techniques were already known at the start of this project (e.g. HiP-HOPS), the research focuses on the optimisation task.The thesis reviews the process of safety integrity requirements allocation and presents relevant related work. Then, the state-of-the-art of metaheuristic optimisation is analysed and a series of techniques, based on Genetic Algorithms, the Particle Swarm Optimiser and Tabu Search are developed. These techniques are applied to a set of problems based on complex engineering systems considering the use of different cost functions. The most promising method is selected for investigation of performance improvements and usability enhancements. Overall, the results show the feasibility of the approach and suggest good scalability whilst also pointing towards areas for improvement

Horizontes da Avaliação em Tecnologias da Saúde

Tomando como pano de fundo as recomendações da International Network of Agencies for Health Technology Assessment (INAHTA) e as propostas de trabalho do Danish Centre of Health Technology Assessment - National Board of Health, os autores colocam em ênfase que a avaliação em tecnologias da saúde (ATS) é um campo de estudos multidisciplinares, cujos resultados comportam diversas implicações clínicas, sociais, culturais, políticas, éticas e económicas no domínio do desenvolvimento, difusão e utilização das tecnologias na prestação dos cuidados de saúde. Refutando a mera ideia de que a ATS seja um veículo instrumentalizado para fornecer aos decisores políticos informações sobre os possíveis impactos e as consequências de uma nova tecnologia nos cuidados de saúde, os autores argumentam que é necessário refletir e debater sobre os critérios de ATS, sugerindo para o efeito a adoção dum modelo plural e multidisciplinar do tipo do modelo dinamarquês, tendo o cidadão-utente no centro do sistema de avaliação em tecnologias da saúde

O papel das redes sociais na orientação clínica em estudantes de licenciatura

O ensino clínico e os papéis dos diversos intervenientes constituem um elemento primordial na formação dos alunos, promovendo a sua aprendizagem e consequentemente o seu futuro como profissionais. Este trabalho, visa à identificação e compreensão de determinadas competências e momentos que são valorizados para o sucesso do aluno estagiário de um curso superior, que emergem de conhecimento obtido a partir de redes sociais informais, bem como o nível das expetativas que os atores sociais apresentam em relação à capacidade e desenvolvimento dos mesmos no futuro

Patient safety culture: radiographers’ perception

Research to evaluate radiographers’ perceptions about patient safety culture in Portuguese public and private imaging facilities found that overall perception is positive but the safety culture dimensions rating should guide culture development of safety culture improvement action plans.info:eu-repo/semantics/publishedVersio

Radiographers perceptions of patient safety culture

The purpose of this research was to evaluate the radiographers perception about patient safety culture in public and private facilities nationwide. A web based survey composed by a sociodemographic characterization was added to the translated and validated to portuguese tool. This tool was the Hospital Survey on Patient Safety Culture (HSOPSC). With the development of this research, it was possible to conclude that radiographers have a positive perception of their department, in some dimensions, with greater failures in the areas of "Feedback and communication about errors" and "Workers". Despite the existence of some weaker dimensions, the general security perception of radiographers is positive, with a very good opinion of patient safety at the radiology department

Epidemiologic and clinical characteristics of pregnant women living with HIV/AIDS in a region of Southern Brazil where the subtype C of HIV-1 infection predominates

AbstractSouthern Brazil has the highest prevalence rate of AIDS in the country and is the only region in the Americas where HIV-1 subtype C prevails.ObjectiveWe evaluated the epidemiologic and clinical characteristics of pregnant women living with HIV/AIDS in the South region of Santa Catarina, Brazil.MethodsAll pregnant women with HIV infection attending the obstetric outpatient clinic of Criciúma, State of Santa Catarina, in 2007 (n=46) were invited to participate. Data of 36 eligible participants were obtained through a standardized questionnaire.ResultsThe great majority were young, with a steady partner, low family income, low education level and referring early first sexual intercourse. Many reported use of illicit non-injecting drugs (55.5%) and unprotected sex with partners that were HIV-positive (57.7%), injecting drug user (22.2%), male inmate (19.4%), truck driver (13.8%), with history of sexually transmitted disease (11.1%) or men who have sex with men (MSM) (2.8%). Most (66.7%) of the participants had their HIV diagnosis done during the pregnancy, 7 (19.4%) had a previous history of HIV mother-to-child transmission. Therapy based on highly active antiretroviral therapy (94%) was initiated at 19.3 weeks on average and 33% showed irregular antiretroviral adherence.ConclusionThese results confirm previous data on HIV epidemiology in Brazil and suggest that the women partners’ sexual behavior and unprotected sexual intercourse are important aspects of HIV epidemic. Additional efforts in education, prophylaxis and medication adherence are needed

Social media data from two iconic Neotropical big cats: can this translate to action?

IntroductionThere has been a gradual increase in studies of social media data usage in biodiversity conservation. Social media data is an underused source of information with the potential to maximize the outcomes of established conservation measures. In this study, we assessed how structured social media data can provide insight into species conservation through a species conservation plan, based on predefined actions. MethodsWe established a framework centered on a set of steps that go from defining social media platforms and species of interest to applying general analysis of data based on data dimensions—three W’s framework (What, When, Who) and the public engagement that posts received. The final and most important step in our proposed framework is to assess the overlap between social media data outcomes and measures established in conservation plans. In our study, we used the Brazilian National Action Plan (BNAP) for big cats as our model. We extracted posts and metrics about jaguars (Panthera onca) and pumas (Puma concolor) from two social media platforms, Facebook and Twitter. ResultsWe obtained 159 posts for both jaguars and pumas on Facebook (manually) and 23,869 posts for the jaguar and 14,675 posts for the puma on Twitter (through an application user interface). Data were categorized for content and users (only Facebook data) based on analysis of the content obtained and similarities found between posts. We used descriptive statistics for analyzing the metrics extracted for each data dimension (what, when, who, and engagement). We also used algorithms to predict categories in the Twitter database. Our most important findings were based on the development of a matrix summarizing the overlapping actions and dimensions of the data. Our findings revealed that the most prominent category of information for jaguars on Facebook was the sighting of wildlife outside protected areas, while for pumas, it was the trespassing of property by wildlife. From the Twitter dataset, we observed that the most prominent category of information for jaguars was: the sighting of wildlife outside protected areas, while for pumas, it was wildlife depredation by direct or indirect means. We found temporal trends that highlight the importance of categories in understanding information peaks on Facebook and Twitter. DiscussionWhen we analyze online engagement, we see a predominance of positive reactions on Facebook, and on Twitter, we see a balanced reaction between positive and negative. We identified 10 of 41 actions in the BNAP that might benefit from social media data. Most of the actions that could benefit from our dataset were linked to human–wildlife conflicts and threats, such as wildlife–vehicle collisions. Communication and educational actions could benefit from all dimensions of the data. Our results highlight the variety of information on social media to inform conservation programs and their application to conservation actions. We believe that studies on the success of applying data to conservation measures are the next step in this process and could benefit from input from decision-makers

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio