CCR: seu papel no financiamento à infra-estrutura

Bibliografia: p. 113-114.A América Latina constitui um dos principais destinos das exportações brasileiras de bens e serviços com alto valor agregado. A região é uma das prioridades da política externa brasileira, com destaque para a integração física e econômica da América do Sul, a qual requer investimentos em setores como energia e transporte. O Convênio de Pagamentos e Créditos Recíprocos (CCR) da Associação Latino- Americana de Integração (Aladi) tem cumprido importante papel na viabilização de financiamentos a esses investimentos. O CCR é subscrito pelos bancos centrais de 12 países da América Latina, por meio do qual são cursados e compensados os pagamentos derivados do comércio intra-regional. Os financiamentos a projetos de infra-estrutura cursados no Convênio correspondem, essencialmente, ao apoio do governo brasileiro às exportações de bens e serviços para países da região. O presente artigo apresenta uma descrição do funcionamento do CCR e de sua regulamentação nos países signatários.Latin America is one of the leading destinations of Brazilian exports of high added value goods and services. This region is one of the priorities in the Brazilian external policy, with special focus on the physical and economic integration of South America, which requires investments in energy and transport industries. The Agreement on Reciprocal Payments and Credits (CCR) of Associação Latino-Americana de Integração (Latin American Association for Integration - Aladi) has been playing a key role in the financing for these investments. The CCR is subscribed by central banks from 12 Latin American countries, through which regional trade payments are made and cleared. Financing to infrastructure projects covered by the Agreement essentially correspond to the Brazilian government's support to export of goods and services to neighboring countries. This article presents a description of how CCR and its regulation in signatory countries

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

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

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Determinação do índice de qualidade subsuperficial em um Latossolo Amarelo Coeso dos Tabuleiros Costeiros, sob floresta natural Determination of the subsurface quality index in a Cohesive Argisolic Yellow Latosol under natural forest in Coastal Plains

O solo é um recurso natural fundamental para a vida. Sua capacidade para funcionar como substrato para vegetais, filtro ambiental, regulador de fluxo de gases, água e energia é definida como qualidade do solo, cuja quantificação pode ser feita via estabelecimento de um índice numérico, que permite monitorar os efeitos do uso agrícola nos atributos e propriedades do solo. O objetivo do presente trabalho foi determinar o índice de qualidade do solo (IQS) para os horizontes subsuperficiais em um Latossolo Amarelo coeso argissólico (LAx) dos Tabuleiros Costeiros, sob floresta natural. A área estudada localiza-se em uma reserva de Mata Atlântica situada no município de Cruz das Almas-BA, e as amostras foram coletadas em um grid de 18 x 8 m, com espaçamento regular de 2 m, resultando em 50 repetições. Para determinação do índice de qualidade do solo, foram avaliados 11 indicadores de qualidade: macroporosidade, densidade do solo, condutividade hidráulica saturada, retenção de água a -33 kPa (Uv33/PT), relação de disponibilidade de água no solo (AD/PT), pH, resistência à penetração (RP), capacidade de troca catiônica (CTC), percentagem de saturação por bases (V), percentagem de saturação por alumínio (m) e teor de matéria orgânica (MO), agrupados em três funções principais: crescimento radicular em profundidade (CRP), condução e armazenamento de água (CAA) e suprimento de nutrientes (SN). O valor do IQS foi de 0,4620, indicando que o solo possui baixa qualidade para produção vegetal e seu uso em sistemas agrícolas exige melhorias nos indicadores de qualidade para o suprimento de nutrientes e condução e armazenamento de água.Soil is an essential natural resource for life. Its overall capacity to function as substratum for plants, as environmental filter and regulator of gas, water and energy flow is defined as soil quality. An soil quality index can be used to monitor the effects of agricultural use on the soil attributes. The objective of this study was to determine a soil quality index (SQI) for the subsurface horizons of a cohesive argisolic Yellow Latosol (LAx) of Coastal Plains under natural forest. The study area was located in the natural reserve of the Atlantic Forest in Cruz das Almas-BA, Brazil. The samples were collected in a 18 x 8 m grid at a regular distance of 2 m, with 50 replications. To determine the SQI, 11 quality indicators were evaluated: macroporosity, soil density, saturated hydraulic conductivity, water retention at -33 kPa (Uv33/TP), relationship of water availability in the soil (WA/TP), pH, penetration resistance, cation exchange capacity (CEC), base saturation (V %), aluminum saturation (m %), and organic matter. These indicators were grouped based on three main functions: root growth in depth; water conduction and storage; and nutrient supply. The SQI value was 0.4620, which indicates a soil of poor quality for crop production. The SQI index suggests that nutrient supply, water conduction and storage must be improved for the use of this soil in agricultural systems

Envolvimento hepático na sarcoidose: relato de caso Liver involvement in sarcoidosis: a case report

A sarcoidose representa uma doença inflamatória cuja etiologia permanece desconhecida. Acomete principalmente o interstício pulmonar, com formação de granulomas não caseosos e adenomegalia. Trata-se de enfermidade sistêmica, portanto, pode atingir qualquer órgão ou sistema, devendo ser lembrada no diagnóstico diferencial das doenças infecciosas, neoplásicas ou auto-imunes, isto porque, se diagnosticada corretamente, evita medicações ou cirurgias desnecessárias. Os autores relatam um caso de sarcoidose pulmonar com envolvimento hepático, no qual o paciente desenvolveu cirrose e trombose de veia porta.<br>Sarcoidosis is an inflammatory disease whose etiology remains unknown. It is characterized by the formation of non-caseating granulomas and adenopathy, mainly in the pulmonary interstice. This is a systemic disease that may affect any organ or system and should be included in the differential diagnosis of infectious, neoplastic or autoimmune diseases as a correct diagnosis avoids unnecessary surgeries or administration of drugs. The authors report a case of pulmonary sarcoidosis with hepatic involvement in which the patient has developed cirrhosis and portal vein thrombosis

ATLANTIC BIRD TRAITS: a data set of bird morphological traits from the Atlantic forests of South America

Scientists have long been trying to understand why the Neotropical region holds the highest diversity of birds on Earth. Recently, there has been increased interest in morphological variation between and within species, and in how climate, topography, and anthropogenic pressures may explain and affect phenotypic variation. Because morphological data are not always available for many species at the local or regional scale, we are limited in our understanding of intra- and interspecies spatial morphological variation. Here, we present the ATLANTIC BIRD TRAITS, a data set that includes measurements of up to 44 morphological traits in 67,197 bird records from 2,790 populations distributed throughout the Atlantic forests of South America. This data set comprises information, compiled over two centuries (1820–2018), for 711 bird species, which represent 80% of all known bird diversity in the Atlantic Forest. Among the most commonly reported traits are sex (n = 65,717), age (n = 63,852), body mass (n = 58,768), flight molt presence (n = 44,941), molt presence (n = 44,847), body molt presence (n = 44,606), tail length (n = 43,005), reproductive stage (n = 42,588), bill length (n = 37,409), body length (n = 28,394), right wing length (n = 21,950), tarsus length (n = 20,342), and wing length (n = 18,071). The most frequently recorded species are Chiroxiphia caudata (n = 1,837), Turdus albicollis (n = 1,658), Trichothraupis melanops (n = 1,468), Turdus leucomelas (n = 1,436), and Basileuterus culicivorus (n = 1,384). The species recorded in the greatest number of sampling localities are Basileuterus culicivorus (n = 243), Trichothraupis melanops (n = 242), Chiroxiphia caudata (n = 210), Platyrinchus mystaceus (n = 208), and Turdus rufiventris (n = 191). ATLANTIC BIRD TRAITS (ABT) is the most comprehensive data set on measurements of bird morphological traits found in a biodiversity hotspot; it provides data for basic and applied research at multiple scales, from individual to community, and from the local to the macroecological perspectives. No copyright or proprietary restrictions are associated with the use of this data set. Please cite this data paper when the data are used in publications or teaching and educational activities. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ