MOOC: UM NOVO MODELO DE UNIVERSIDADES?

Tem-se observado uma tendência na redefinição da gestão do conhecimento e da produção em nossa sociedade, onde se percebe um maior direcionamento do conhecimento como fator de inovação e competitividade das empresas, aliados a um contexto de mudanças sociais, políticas, demográfica, econômica e tecnológica, que por sua vez, também impulsionam mudanças na educação. Ao que parece as fortalezas da encastelada universidade, detentora até então da criação e da difusão universal do conhecimento humano, e da formação superior, começam a encontrar substitutos e assim, sem mais, defrontam-se com as suas fragilidades, cada vez mais necessárias e reclamadas pela sociedade. Este estudo buscou como fontes de consultas tanto as de origem acadêmica quanto as disponíveis na mídia especializada. A busca por artigos não acadêmicos se deve a dois fatores, primeiro pela escassa existência de artigos e livros que tratem dos temas em questão, assim como também pelo enfoque de sondar junto à mídia de massa, como estão sendo tratados os temas de estudo, além dos muros da academia. Uma discussão sobre os fatores que estão proporcionando essas mudanças e em especial a influência do movimento MOOC nas universidades é o objetivo a que se propõe este estudo

Shrimp farming: Where does the carbon go?

Abstract The muscle tissues of the Litopenaeus vannamei shrimp grown in ponds through organic and traditional (intensive) management show that δ13C values were similar amongst the shrimp. Shrimp grown in the traditional pond were enriched in 13C by 7‰ relative to the carbon isotope ratios of their feed. The differences in the carbon isotope ratios of shrimp and feed in the traditional pond shows that the feed is not the main carbon source for shrimp grown in the traditional intensive management. Using mass balance we calculate that feed in traditional culture contributes at most 13% of the shrimp's carbon biomass

Numerical simulation of the hydrodynamic in the Curimataú estuary, RN Brazil

The Curimataú River estuary is a shallow partially mixed (type 2) tropical estuary, located in the Rio Grande do Norte (RN) state, northeast Brazilian coast (lat. 06o18’S); the main system is composed by three rivers: Curimataú, Cunhaú and Guaratuba. The numerical model Delft3D-Flow was used to study hydrodynamic features of the estuary. The model predictions were evaluated using the Skill parameter based in the comparison of the theoretical solutions with observations of hourly values of tidal heights, currents and salinity at an anchor station located at the cell (M=279; N=323). The applied computational grid is curvilinear with around 6,000 horizontal wet points, including the inner shelf. Open boundary conditions was obtained from the analysis of 2.7 years of hourly tidal heights, recorded at Natal harbor, and the inner boundaries conditions were controlled by freshwater input into the three main rivers. Initial conditions of hydrographic properties were uniform in the previous simulations and, only the temperature was set to a constant value in whole simulation. The steady-state of the fields of velocity and thermohaline properties was reached after almost four weeks of simulation of the baroclinic mode. The best fit between the model and the observations was for the semidiurnal spring tide oscillation with a Skill=0.98; for the velocities and salinities simulations during this tidal condition the best mean Skills values were 0.82 and 0.94, respectively

Produção de um ciclone automatizado e de baixo custo para divulgação do curso de engenharia química em Manaus/ Production of a low-cost automated cyclone for Manaus chemical engineering course

 Em Manaus grande parte dos alunos que terminam o ensino médio escolhem um curso universitário sem o seu respectivo conhecimento. Este trabalho teve como objetivo a construção e automação de um ciclone caseiro, efetuado por discentes da Engenharia Química da UFAM, para demonstração aos alunos do ensino médio. O ciclone foi construído com materiais recicláveis e automatizado com arduino. Os resultados mostraram que 91% dos alunos não tinham conhecimento do curso de Engenharia Química

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

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

Local hydrological conditions influence tree diversity and composition across the Amazon basin

Tree diversity and composition in Amazonia are known to be strongly determined by the water supplied by precipitation. Nevertheless, within the same climatic regime, water availability is modulated by local topography and soil characteristics (hereafter referred to as local hydrological conditions), varying from saturated and poorly drained to well-drained and potentially dry areas. While these conditions may be expected to influence species distribution, the impacts of local hydrological conditions on tree diversity and composition remain poorly understood at the whole Amazon basin scale. Using a dataset of 443 1-ha non-flooded forest plots distributed across the basin, we investigate how local hydrological conditions influence 1) tree alpha diversity, 2) the community-weighted wood density mean (CWM-wd) – a proxy for hydraulic resistance and 3) tree species composition. We find that the effect of local hydrological conditions on tree diversity depends on climate, being more evident in wetter forests, where diversity increases towards locations with well-drained soils. CWM-wd increased towards better drained soils in Southern and Western Amazonia. Tree species composition changed along local soil hydrological gradients in Central-Eastern, Western and Southern Amazonia, and those changes were correlated with changes in the mean wood density of plots. Our results suggest that local hydrological gradients filter species, influencing the diversity and composition of Amazonian forests. Overall, this study shows that the effect of local hydrological conditions is pervasive, extending over wide Amazonian regions, and reinforces the importance of accounting for local topography and hydrology to better understand the likely response and resilience of forests to increased frequency of extreme climate events and rising temperatures