Mobility in Lisbon based on smartphone data

This research covers five months (September, October, November, December 2021, and January 2022) of georeferenced data of the Vodafone mobile phone service, provided by the municipality of Lisbon (CML). The motivation of this research regards the fact that the urban mobility study with mobile phone data is a relatively unexplored topic. This study focused on the city of Lisbon, with a case study conducted in the parish of Santa Maria Maior with the aim to understand the urban mobility patterns of mobile phone users. The number of roaming and non-roaming devices in the case study is related to the subject of a vibrant neighborhood and tourism, characterized by transportation and historical points of interest. We used a data mining approach to analyze mobility trends, adopting a CRISP-DM methodology, to perform statistical analysis, visualization, and clustering (DBSCAN) methods. Results showed eight clusters in Santa Maria Maior, with outstanding clusters along 28-E electric tram and Lisbon Cruise Terminal. Foremost, we looked at these two clusters and performed a forecast model with Prophet, resulting in downward trend, influenced by the pandemic restrictions in December and January data. This thesis contributes considerably to the digital transformation of Lisbon into a smart city by understanding urban mobility patterns with smartphone data of no roaming and roaming users.Este estudo abrange cinco meses (setembro, outubro, novembro, dezembro de 2021 e janeiro de 2022) de dados georreferenciados do serviço da operadora móvel Vodafone, fornecido pela Câmara Municipal de Lisboa (CML). A motivação da tese considera o facto de o estudo da mobilidade urbana com dados de telemóveis ser um tópico relativamente inexplorado. Este estudo centrou-se na cidade de Lisboa, com um caso de estudo na freguesia de Santa Maria Maior com o objetivo de compreender os padrões de mobilidade urbana dos utilizadores da rede móvel. O número de dispositivos de nãoroaming e roaming no caso de estudo está relacionado com o tema das ‘vibrant neighborhoods’ e turismo, caracterizado por pontos de interesse históricos e de transportes. Utilizámos uma abordagem de ‘data mining’ para analisar as tendências de mobilidade, adotando uma metodologia CRISP-DM, para realizar análise estatística, visualização e agrupamentos (DBSCAN). Os resultados mostraram nove agrupamentos em Santa Maria Maior, dos quais dois agrupamentos de destaque, um ao longo do elétrico 28-E e outro à volta do Terminal de Cruzeiros de Lisboa. Em primeiro lugar, analisámos estes dois agrupamentos e realizámos análises de previsão, resultando numa tendência decrescente, como consequência das restrições da pandemia nos meses de dezembro e janeiro. Esta tese contribui consideravelmente para a transformação digital de Lisboa numa cidade inteligente, ao compreender os padrões de mobilidade urbana com dados dos utilizadores da rede móvel em não-roaming e roaming

Geoeconomic variations in epidemiology, ventilation management, and outcomes in invasively ventilated intensive care unit patients without acute respiratory distress syndrome: a pooled analysis of four observational studies

Background: Geoeconomic variations in epidemiology, the practice of ventilation, and outcome in invasively ventilated intensive care unit (ICU) patients without acute respiratory distress syndrome (ARDS) remain unexplored. In this analysis we aim to address these gaps using individual patient data of four large observational studies. Methods: In this pooled analysis we harmonised individual patient data from the ERICC, LUNG SAFE, PRoVENT, and PRoVENT-iMiC prospective observational studies, which were conducted from June, 2011, to December, 2018, in 534 ICUs in 54 countries. We used the 2016 World Bank classification to define two geoeconomic regions: middle-income countries (MICs) and high-income countries (HICs). ARDS was defined according to the Berlin criteria. Descriptive statistics were used to compare patients in MICs versus HICs. The primary outcome was the use of low tidal volume ventilation (LTVV) for the first 3 days of mechanical ventilation. Secondary outcomes were key ventilation parameters (tidal volume size, positive end-expiratory pressure, fraction of inspired oxygen, peak pressure, plateau pressure, driving pressure, and respiratory rate), patient characteristics, the risk for and actual development of acute respiratory distress syndrome after the first day of ventilation, duration of ventilation, ICU length of stay, and ICU mortality. Findings: Of the 7608 patients included in the original studies, this analysis included 3852 patients without ARDS, of whom 2345 were from MICs and 1507 were from HICs. Patients in MICs were younger, shorter and with a slightly lower body-mass index, more often had diabetes and active cancer, but less often chronic obstructive pulmonary disease and heart failure than patients from HICs. Sequential organ failure assessment scores were similar in MICs and HICs. Use of LTVV in MICs and HICs was comparable (42·4% vs 44·2%; absolute difference -1·69 [-9·58 to 6·11] p=0·67; data available in 3174 [82%] of 3852 patients). The median applied positive end expiratory pressure was lower in MICs than in HICs (5 [IQR 5-8] vs 6 [5-8] cm H2O; p=0·0011). ICU mortality was higher in MICs than in HICs (30·5% vs 19·9%; p=0·0004; adjusted effect 16·41% [95% CI 9·52-23·52]; p<0·0001) and was inversely associated with gross domestic product (adjusted odds ratio for a US$10 000 increase per capita 0·80 [95% CI 0·75-0·86]; p<0·0001). Interpretation: Despite similar disease severity and ventilation management, ICU mortality in patients without ARDS is higher in MICs than in HICs, with a strong association with country-level economic status

Brazilian Flora 2020: Leveraging the power of a collaborative scientific network

International audienceThe shortage of reliable primary taxonomic data limits the description of biological taxa and the understanding of biodiversity patterns and processes, complicating biogeographical, ecological, and evolutionary studies. This deficit creates a significant taxonomic impediment to biodiversity research and conservation planning. The taxonomic impediment and the biodiversity crisis are widely recognized, highlighting the urgent need for reliable taxonomic data. Over the past decade, numerous countries worldwide have devoted considerable effort to Target 1 of the Global Strategy for Plant Conservation (GSPC), which called for the preparation of a working list of all known plant species by 2010 and an online world Flora by 2020. Brazil is a megadiverse country, home to more of the world's known plant species than any other country. Despite that, Flora Brasiliensis, concluded in 1906, was the last comprehensive treatment of the Brazilian flora. The lack of accurate estimates of the number of species of algae, fungi, and plants occurring in Brazil contributes to the prevailing taxonomic impediment and delays progress towards the GSPC targets. Over the past 12 years, a legion of taxonomists motivated to meet Target 1 of the GSPC, worked together to gather and integrate knowledge on the algal, plant, and fungal diversity of Brazil. Overall, a team of about 980 taxonomists joined efforts in a highly collaborative project that used cybertaxonomy to prepare an updated Flora of Brazil, showing the power of scientific collaboration to reach ambitious goals. This paper presents an overview of the Brazilian Flora 2020 and provides taxonomic and spatial updates on the algae, fungi, and plants found in one of the world's most biodiverse countries. We further identify collection gaps and summarize future goals that extend beyond 2020. Our results show that Brazil is home to 46,975 native species of algae, fungi, and plants, of which 19,669 are endemic to the country. The data compiled to date suggests that the Atlantic Rainforest might be the most diverse Brazilian domain for all plant groups except gymnosperms, which are most diverse in the Amazon. However, scientific knowledge of Brazilian diversity is still unequally distributed, with the Atlantic Rainforest and the Cerrado being the most intensively sampled and studied biomes in the country. In times of “scientific reductionism”, with botanical and mycological sciences suffering pervasive depreciation in recent decades, the first online Flora of Brazil 2020 significantly enhanced the quality and quantity of taxonomic data available for algae, fungi, and plants from Brazil. This project also made all the information freely available online, providing a firm foundation for future research and for the management, conservation, and sustainable use of the Brazilian funga and flora