Wear and friction behaviour of Si3N4 ceramics under diesel and biodiesel lubrication

The wear and friction behaviour of self-mated silicon nitride pairs in lubricated ball-on-flat reciprocating sliding conditions is the subject of the present work, using diesel fuel and soybean biodiesels as lubricants. The results show that the friction coefficient is considerably higher for the diesel fuel than for biodiesels in the stationary regime (about 0.14 and 0.06, respectively). The wear coefficient values are in the range 10−8–10−9 mm3/N·m, denoting a mild wear regime, in agreement with the high lubricity of these fuels assessed by the ASTM D 6079 standard. The observed wear mechanisms were mainly mechanically dominated, consisting of transgranular and intergranular fractures, and the formation of a tribolayer by plastic deformation of the wear debris

Genomic, epidemiological and digital surveillance of Chikungunya virus in the Brazilian Amazon.

BackgroundSince its first detection in the Caribbean in late 2013, chikungunya virus (CHIKV) has affected 51 countries in the Americas. The CHIKV epidemic in the Americas was caused by the CHIKV-Asian genotype. In August 2014, local transmission of the CHIKV-Asian genotype was detected in the Brazilian Amazon region. However, a distinct lineage, the CHIKV-East-Central-South-America (ECSA)-genotype, was detected nearly simultaneously in Feira de Santana, Bahia state, northeast Brazil. The genomic diversity and the dynamics of CHIKV in the Brazilian Amazon region remains poorly understood despite its importance to better understand the epidemiological spread and public health impact of CHIKV in the country.Methodology/principal findingsWe report a large CHIKV outbreak (5,928 notified cases between August 2014 and August 2018) in Boa vista municipality, capital city of Roraima's state, located in the Brazilian Amazon region. We generated 20 novel CHIKV-ECSA genomes from the Brazilian Amazon region using MinION portable genome sequencing. Phylogenetic analyses revealed that despite an early introduction of the Asian genotype in 2015 in Roraima, the large CHIKV outbreak in 2017 in Boa Vista was caused by an ECSA-lineage most likely introduced from northeastern Brazil. Epidemiological analyses suggest a basic reproductive number of R0 of 1.66, which translates in an estimated 39 (95% CI: 36 to 45) % of Roraima's population infected with CHIKV-ECSA. Finally, we find a strong association between Google search activity and the local laboratory-confirmed CHIKV cases in Roraima.Conclusions/significanceThis study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region. Our data reveal a large CHIKV-ECSA outbreak in Boa Vista, limited potential for future CHIKV outbreaks, and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region

Chikungunya virus outbreak in the Amazon region: replacement of the Asian genotype by an ECSA lineage

Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Laboratório de Ecologia de Doenças Transmissíveis na Amazônia. Manaus, AM, Brazil.Universidade de São Paulo. Faculdade de Medicina. Instituto de Medicina Tropical. São Paulo, SP, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil / Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Patologia Experimental. Salvador, BA, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil / Fundação Oswaldo Cruz. Instituto Gonçalo Moniz. Laboratório de Patologia Experimental. Salvador, BA, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil / Fundação Ezequiel Dias. Instituto Octávio Magalhães. Laboratório Central de Saúde Pública. Belo Horizonte, MG, Brazil.Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Laboratório de Ecologia de Doenças Transmissíveis na Amazônia. Manaus, AM, Brazil.Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Laboratório de Ecologia de Doenças Transmissíveis na Amazônia. Manaus, AM, Brazil.Universidade Federal do Rio de Janeiro. Instituto de Biologia. Departamento de Genética Laboratório de Virologia Molecular. Rio de Janeiro, RJ, Brazil.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.Harvard Medical School. Department of Pediatrics. Boston, MA, USA / Boston Children’s Hospital. Computational Health Informatics Program. Boston, MA, USA.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom / Boston Children’s Hospital. Computational Epidemiology Lab. Boston, MA, USA.University of Birmingham. Institute of Microbiology and Infection. Birmingham, United Kingdom.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.Universidade de São Paulo. Faculdade de Medicina. Instituto de Medicina Tropical. São Paulo, SP, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Centro de Inovações Tecnológicas. Ananindeua, PA, Brasil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Instituto Evandro Chagas. Centro de Inovações Tecnológicas. Ananindeua, PA, Brasil.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.Laboratório Central de Saúde Pública. Boa Vista, RR, Brazil.Laboratório Central de Saúde Pública. Boa Vista, RR, Brazil.Laboratório Central de Saúde Pública. Boa Vista, RR, Brazil.Secretaria Municipal de Saúde de Boa Vista. Superintendência de Vigilância em Saúde. Boa Vista, RR, Brazil.Fundação de Medicina Tropical Doutor Heitor Vieira. Departamento de Virologia. Manaus, AM, Brazil.Secretaria Municipal de Saúde de Boa Vista. Superintendência de Vigilância em Saúde. Boa Vista, RR, Brazil.Laboratório Central de Saúde Pública do Amazonas. Manaus, AM, Brazil.Organização Pan - Americana da Saúde/Organização Mundial da Saúde. Brasília, DF, BrazilMinistério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Fundação Oswaldo Cruz. Instituto Leônidas e Maria Deane. Laboratório de Ecologia de Doenças Transmissíveis na Amazônia. Manaus, AM, Brazil.University of Birmingham. Institute of Microbiology and Infection. Birmingham, United Kingdom.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.Universidade de São Paulo. Faculdade de Medicina. Instituto de Medicina Tropical. São Paulo, SP, Brazil.Ministério da Saúde. Secretaria de Vigilância em Saúde. Brasília, DF, Brazil.Fundação Oswaldo Cruz. Instituto Oswaldo Cruz. Laboratório de Flavivírus. Rio de Janeiro, RJ, Brazil / Universidade Federal de Minas Gerais. Instituto de Ciências Biológicas. Laboratório de Genética Celular e Molecular. Belo Horizonte, MG, Brazil.University of Oxford. Department of Zoology. South Parks Road, Oxford, United Kingdom.Background Since its first detection in the Caribbean in late 2013, chikungunya virus (CHIKV) has affected 51 countries in the Americas. The CHIKV epidemic in the Americas was caused by the CHIKV-Asian genotype. In August 2014, local transmission of the CHIKV-Asian genotype was detected in the Brazilian Amazon region. However, a distinct lineage, the CHIKV-East-Central-South-America (ECSA)-genotype, was detected nearly simultaneously in Feira de Santana, Bahia state, northeast Brazil. The genomic diversity and the dynamics of CHIKV in the Brazilian Amazon region remains poorly understood despite its importance to better understand the epidemiological spread and public health impact of CHIKV in the country. Methodology/Principal Findings We report a large CHIKV outbreak (5,928 notified cases between August 2014 and August 2018) in Boa vista municipality, capital city of Roraima’s state, located in the Brazilian Amazon region. In just 48 hours, we generated 20 novel CHIKV-ECSA genomes from the Brazilian Amazon region using MinION portable genome sequencing. Phylogenetic analyses revealed that despite an early introduction of the Asian genotype in 2015 in Roraima, the large CHIKV outbreak in 2017 in Boa Vista was caused by an ECSA-lineage most likely introduced from northeastern Brazil. Epidemiological analyses suggest a basic reproductive number of R0 of 1.66, which translates in an estimated 39 (95% CI: 36 to 45) % of Roraima’s population infected with CHIKV-ECSA. Finally, we find a strong association between Google search activity and the local laboratory-confirmed CHIKV cases in Roraima. Conclusions/Significance This study highlights the potential of combining traditional surveillance with portable genome sequencing technologies and digital epidemiology to inform public health surveillance in the Amazon region. Our data reveal a large CHIKV-ECSA outbreak in Boa Vista, limited potential for future CHIKV outbreaks, and indicate a replacement of the Asian genotype by the ECSA genotype in the Amazon region

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

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