Eça de Queiroz e o Brasil ou o sentimento impossível

Este ensaio questiona como um romancista da grandeza de Eça de Queiroz, de nacionalidade portuguesa, pode ser tão admirado e cultuado pelos brasilei­ros. E, o que reria levado o público leitor a se reconhecer de modo tão forre na obra queirosiana? A identificação, de faro, deu-se a níveis profundos pois toca­va em feridas comuns, defeitos partilhados e heranças indivisas. Assim, a rela­ção de intimidade e cumplicidade transcendeu a literatura se inscrevendo na própria vida. Baseado na crítica literária, o ensaísta conclui que a força de Eça reside no encantamento da sua escrita. Eça persuadiu os seus leitores portu­gueses e brasileiros que somos realmente figuras de seus romances. Dessa for­ma, o leitor brasileiro recebeu Eça com afeto, intimidade e estabeleceu com a sua obra uma identificação absoluta. A história da recepção de Eça de Queiroz no Brasil é extraordinária. Basta mencionar Monteiro Lobato que assim se ex­primia: "Chegamos quase à conclusão que ele privara conosco". Essa intimida­de vivida a que Clóvis Ramalhete chamava "um sentimento impossível por Eça de Queiroz". Contudo, Eça tinha uma relação com um Brasil imaginário, iden­tificado com amigos da elice brasileira da época. Foi, portanto, condicionado por amigos notáveis, cultos, lúcidos e apaixonadamente europeizados. Este foi o Brasil que ele conheceu e amou. O público leitor brasileiro tinha entusiasmo pela sua obra e um sentimento impossível de saudade

PORTUGAL E O BRASIL: Atribulações de duas identidades

Escrito por Luís Filipe Castro Mendes

1798: GONZAGA NA ILHA DE MOÇAMBIQUE

É possível que algum dia eu tenha esquecido: Marília te chamava, Mil te digo agora, como mil chamas a arder em redor de um coração maior que o mundo

Pre-heating boiler feedwater for expanded cork agglomerate production using a parabolic trough system

ABSTRACT: The production of expanded cork agglomerate involves significant heat demand, requiring superheated steam at temperatures ranging from 300°C to 370°C. The energy required to this process can be suitably provided by concentrating solar thermal collectors. This work considers the thermal energy needs of a real plant, presenting the technical and economical analysis performed for a solar heat for industrial process system using parabolic trough collectors to preheat the feedwater used by the boiler providing steam to the expanded cork agglomerate production process.info:eu-repo/semantics/publishedVersio

Building a Portuguese Coalition for Biodiversity Genomics

The diverse physiography of the Portuguese land and marine territory, spanning from continental Europe to the Atlantic archipelagos, has made it an important repository of biodiversity throughout the Pleistocene glacial cycles, leading to a remarkable diversity of species and ecosystems. This rich biodiversity is under threat from anthropogenic drivers, such as climate change, invasive species, land use changes, overexploitation or pathogen (re)emergence. The inventory, characterization and study of biodiversity at inter- and intra-specific levels using genomics is crucial to promote its preservation and recovery by informing biodiversity conservation policies, management measures and research. The participation of researchers from Portuguese institutions in the European Reference Genome Atlas (ERGA) initiative, and its pilot effort to generate reference genomes for European biodiversity, has reinforced the establishment of Biogenome Portugal. This nascent institutional network will connect the national community of researchers in genomics. Here, we describe the Portuguese contribution to ERGA’s pilot effort, which will generate high-quality reference genomes of six species from Portugal that are endemic, iconic and/or endangered, and include plants, insects and vertebrates (fish, birds and mammals) from mainland Portugal or the Azores islands. In addition, we outline the objectives of Biogenome Portugal, which aims to (i) promote scientific collaboration, (ii) contribute to advanced training, (iii) stimulate the participation of institutions and researchers based in Portugal in international biodiversity genomics initiatives, and (iv) contribute to the transfer of knowledge to stakeholders and engaging the public to preserve biodiversity. This initiative will strengthen biodiversity genomics research in Portugal and fuel the genomic inventory of Portuguese eukaryotic species. Such efforts will be critical to the conservation of the country’s rich biodiversity and will contribute to ERGA’s goal of generating reference genomes for European species.info:eu-repo/semantics/publishedVersio

MAMMALS IN PORTUGAL : A data set of terrestrial, volant, and marine mammal occurrences in P ortugal

Mammals are threatened worldwide, with 26% of all species being includedin the IUCN threatened categories. This overall pattern is primarily associatedwith habitat loss or degradation, and human persecution for terrestrial mam-mals, and pollution, open net fishing, climate change, and prey depletion formarine mammals. Mammals play a key role in maintaining ecosystems func-tionality and resilience, and therefore information on their distribution is cru-cial to delineate and support conservation actions. MAMMALS INPORTUGAL is a publicly available data set compiling unpublishedgeoreferenced occurrence records of 92 terrestrial, volant, and marine mam-mals in mainland Portugal and archipelagos of the Azores and Madeira thatincludes 105,026 data entries between 1873 and 2021 (72% of the data occur-ring in 2000 and 2021). The methods used to collect the data were: live obser-vations/captures (43%), sign surveys (35%), camera trapping (16%),bioacoustics surveys (4%) and radiotracking, and inquiries that represent lessthan 1% of the records. The data set includes 13 types of records: (1) burrowsjsoil moundsjtunnel, (2) capture, (3) colony, (4) dead animaljhairjskullsjjaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8),observation in shelters, (9) photo trappingjvideo, (10) predators dietjpelletsjpine cones/nuts, (11) scatjtrackjditch, (12) telemetry and (13) vocalizationjecholocation. The spatial uncertainty of most records ranges between 0 and100 m (76%). Rodentia (n=31,573) has the highest number of records followedby Chiroptera (n=18,857), Carnivora (n=18,594), Lagomorpha (n=17,496),Cetartiodactyla (n=11,568) and Eulipotyphla (n=7008). The data setincludes records of species classified by the IUCN as threatened(e.g.,Oryctolagus cuniculus[n=12,159],Monachus monachus[n=1,512],andLynx pardinus[n=197]). We believe that this data set may stimulate thepublication of other European countries data sets that would certainly contrib-ute to ecology and conservation-related research, and therefore assisting onthe development of more accurate and tailored conservation managementstrategies for each species. There are no copyright restrictions; please cite thisdata paper when the data are used in publications.info:eu-repo/semantics/publishedVersio

Mammals in Portugal: a data set of terrestrial, volant, and marine mammal occurrences in Portugal

Mammals are threatened worldwide, with ~26% of all species being included in the IUCN threatened categories. This overall pattern is primarily associated with habitat loss or degradation, and human persecution for terrestrial mammals, and pollution, open net fishing, climate change, and prey depletion for marine mammals. Mammals play a key role in maintaining ecosystems functionality and resilience, and therefore information on their distribution is crucial to delineate and support conservation actions. MAMMALS IN PORTUGAL is a publicly available data set compiling unpublished georeferenced occurrence records of 92 terrestrial, volant, and marine mammals in mainland Portugal and archipelagos of the Azores and Madeira that includes 105,026 data entries between 1873 and 2021 (72% of the data occurring in 2000 and 2021). The methods used to collect the data were: live observations/captures (43%), sign surveys (35%), camera trapping (16%), bioacoustics surveys (4%) and radiotracking, and inquiries that represent less than 1% of the records. The data set includes 13 types of records: (1) burrows | soil mounds | tunnel, (2) capture, (3) colony, (4) dead animal | hair | skulls | jaws, (5) genetic confirmation, (6) inquiries, (7) observation of live animal (8), observation in shelters, (9) photo trapping | video, (10) predators diet | pellets | pine cones/nuts, (11) scat | track | ditch, (12) telemetry and (13) vocalization | echolocation. The spatial uncertainty of most records ranges between 0 and 100 m (76%). Rodentia (n =31,573) has the highest number of records followed by Chiroptera (n = 18,857), Carnivora (n = 18,594), Lagomorpha (n = 17,496), Cetartiodactyla (n = 11,568) and Eulipotyphla (n = 7008). The data set includes records of species classified by the IUCN as threatened (e.g., Oryctolagus cuniculus [n = 12,159], Monachus monachus [n = 1,512], and Lynx pardinus [n = 197]). We believe that this data set may stimulate the publication of other European countries data sets that would certainly contribute to ecology and conservation-related research, and therefore assisting on the development of more accurate and tailored conservation management strategies for each species. There are no copyright restrictions; please cite this data paper when the data are used in publications

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