Perceived image of Portugal by swedish tourists

Mestrado em MarketingO turismo desempenha um papel importante na economia Portuguesa. Todos os esforços para aumentar o número de turistas que chegam a Portugal tem sido reconhecidos em todo o mundo através de prémios e ocupar o primeiro lugar das melhores cidades europeias a visitar. No entanto, a imagem de Portugal não tem muito impacto sobre certos países, como a Suécia. Imagem do destino turístico é um assunto muito importante e discutido na literatura turismo. O objetivo deste estudo é compreender os atributos que os suecos consideram na escolha do destino turístico, perceber também a imagem percecionada de Portugal para consequentemente sugerir estratégias para aumentar a comunicação de Portugal na Suécia. Depois de fazer uma breve revisão da literatura, o modelo seguido foi o Echtner & Ritchie (1993), modelo Tridimensional, que inclui os atributos funcionais (tangíveis) e os atributos psicológicos (intangíveis) que permitem ter uma análise completa da imagem percebida de Portugal. Os resultados mostram que os turistas suecos procuram um destino agradável para se divertirem, conhecer a cultura e a história e, principalmente, tem em consideração o clima do destino turístico. A imagem percebida de Portugal é positiva na maioria dos atributos tangíveis e intangíveis avaliados. Finalmente, a comunicação deve ser feita na Internet através de campanhas em jornais e revistas online, através das redes sociais e blogs.Tourism plays an important role in the Portuguese economy. All efforts to increase the number of tourists arriving in Portugal has been recognized worldwide by awards and Lisbon occupies the first place on the rank of the best European cities to visit. However, the image of Portugal does not have that much of an impact on certain countries, such as Sweden. The image of tourist destination is a very important topic discussed in tourism literature. The aim of this study is to understand the attributes that Swedish people consider while choosing their destination, to find out the perceived image of Portugal and, therefore, suggest strategies to increase the communication of Portugal in Sweden. After making a brief literature review, the model followed was the Echtner & Ritchie (1993), Tri-dimensional model, which includes the functional attributes (tangible) and psychological attributes (intangible) that allows to have a complete analysis of the perceived image of Portugal. The results showed that the Swedish tourists look for in a destination to have a good time, get to know the culture and history and specially they take into account the weather of the destination. The perceived image of Portugal is positive in most of the tangible and intangible attributes evaluated. Finally, the communication should be done over internet through campaigns on magazines and newspapers, using social media and blogs

Displasia do desenvolvimento do quadril - uma revisão abrangente sobre a epidemiologia, anatomia, etiologia, aspectos genéticos, diagnóstico, tratamento, prognóstico e prevenção

A displasia do desenvolvimento do quadril (DDQ) é uma condição ortopédica comum em lactentes e crianças, caracterizada por anormalidades na articulação do quadril. Sua incidência varia em diferentes regiões geográficas, mas estima-se que afete cerca de 1 a 3 em cada 100 recém-nascidos, sendo mais frequente em meninas e bebês com histórico familiar de DDQ. Essa articulação complexa é composta pelo osso do quadril (osso ilíaco), a cabeça femoral e o acetábulo. A DDQ ocorre devido a desarmonias na formação dessas estruturas, o que acarreta má posição e estabilidade inadequada do quadril. Quanto à etiologia, múltiplos fatores genéticos, ambientais e mecânicos contribuem para o desenvolvimento da DDQ, incluindo posição intrauterina, primeira gravidez e posição do feto. O diagnóstico precoce é crucial para o tratamento eficaz da condição, sendo o exame físico e métodos de imagem, como ultrassonografia do quadril em recém-nascidos e radiografia em bebês mais velhos, fundamentais para determinar a gravidade da displasia. O tratamento varia conforme a gravidade e a idade do paciente, com opções que vão desde dispositivos ortopédicos, como o coxal de Pavlik, em casos leves a moderados, até a cirurgia corretiva para casos mais graves ou tardios. O prognóstico geralmente é positivo quando o diagnóstico é precoce e o tratamento adequado é instituído, evitando complicações a longo prazo, como osteoartrite e dor crônica. Por fim, a prevenção é essencial por meio do rastreamento adequado em exames de rotina, exames clínicos cuidadosos e conscientização dos pais sobre os fatores de risco, a fim de assegurar o desenvolvimento adequado do quadril e o tratamento bem-sucedido da DDQ

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

Design and baseline characteristics of the finerenone in reducing cardiovascular mortality and morbidity in diabetic kidney disease trial

Background: Among people with diabetes, those with kidney disease have exceptionally high rates of cardiovascular (CV) morbidity and mortality and progression of their underlying kidney disease. Finerenone is a novel, nonsteroidal, selective mineralocorticoid receptor antagonist that has shown to reduce albuminuria in type 2 diabetes (T2D) patients with chronic kidney disease (CKD) while revealing only a low risk of hyperkalemia. However, the effect of finerenone on CV and renal outcomes has not yet been investigated in long-term trials. Patients and Methods: The Finerenone in Reducing CV Mortality and Morbidity in Diabetic Kidney Disease (FIGARO-DKD) trial aims to assess the efficacy and safety of finerenone compared to placebo at reducing clinically important CV and renal outcomes in T2D patients with CKD. FIGARO-DKD is a randomized, double-blind, placebo-controlled, parallel-group, event-driven trial running in 47 countries with an expected duration of approximately 6 years. FIGARO-DKD randomized 7,437 patients with an estimated glomerular filtration rate >= 25 mL/min/1.73 m(2) and albuminuria (urinary albumin-to-creatinine ratio >= 30 to <= 5,000 mg/g). The study has at least 90% power to detect a 20% reduction in the risk of the primary outcome (overall two-sided significance level alpha = 0.05), the composite of time to first occurrence of CV death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for heart failure. Conclusions: FIGARO-DKD will determine whether an optimally treated cohort of T2D patients with CKD at high risk of CV and renal events will experience cardiorenal benefits with the addition of finerenone to their treatment regimen. Trial Registration: EudraCT number: 2015-000950-39; ClinicalTrials.gov identifier: NCT02545049

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 understanding 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,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 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 underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities 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 organism 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 neglected 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 lost

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 understanding 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,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 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 underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities 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 organism 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 neglected 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 lost