Reuso de águas cinzas em empreendimentos comerciais: um estudo de caso em edifício hoteleiro de Belo Horizonte / Reuse of gray water in commercial projects: a case study in a hotel building in Belo Horizonte

As tecnologias de reuso de águas cinzas são soluções sustentáveis e contribuem para uso racional da água, proporcionando a redução da demanda sobre os mananciais de água. A atividade hoteleira pode ser considerada uma das atividades comerciais que mais consomem água, graças a sua complexidade e por necessidades peculiares a este ramo econômico. Portanto, é urgente implementar o uso racional da água, a preservação e o seu reuso nestes ambientes. O estudo apresenta um levantamento sobre a viabilidade econômica de se implementar o reuso de água em um empreendimento hoteleiro de Belo Horizonte e faz uma análise desta prática acerca de sistemas de tratamento que propiciam a recirculação deste efluente, citando suas vantagens e desvantagens.

Análise dos parâmetros de dimensionamento adotados em uma estação de tratamento de esgotos da região metropolitana de Belo Horizonte: um estudo de caso / Analysis of sizing parameters adopted in a sewage treatment plant in the metropolitan region of Belo Horizonte: a case study

O trabalho apresenta um estudo acerca do dimensionamento hidráulico de um sistema de esgotamento sanitário. Além disso, apresenta um estudo de caso sobre uma estação de tratamento de esgotos (ETE) localizada na região metropolitana de Belo Horizonte, Minas Gerais, que foi executado com aplicação de metodologias e parâmetros observados em normas e pela bibliografia pertinente. Este estudo encontra importância na apresentação de dados calculados especificamente para a localidade, que foram analisados comparativamente aos dados adotados no projeto em estudo.

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

The Masticatory Activity Interference in Quantitative Estimation of CA1, CA3 and Dentate Gyrus Hippocampal Astrocytes of Aged Murine Models and under Environmental Stimulation

Studies indicating the influence of masticatory dysfunction, due to a soft diet or lack of molars, on impairing spatial memory and learning have led to research about neuronal connections between areas and cell populations possibly affected. In this sense, with scarce detailed data on the subfields of hippocampus in dementia neurodegeneration, there is no information about astrocytic responses in its different layers. Thus, considering this context, the present study evaluated the effects of deprivation and rehabilitation of masticatory activity, aging, and environmental enrichment on the stereological quantification of hippocampal astrocytes from layers CA1, CA3, and DG. For this purpose, we examined mature (6-month-old; 6M), and aged (18-month-old; 18M) mice, subjected to distinct masticatory regimens and environments. Three different regimens of masticatory activity were applied: continuous normal mastication with hard pellets (HD); normal mastication followed by deprived mastication with equal periods of pellets followed by soft powder (HD/SD); or rehabilitated masticatory activity with equal periods of HD, followed by powder, followed by pellets (HD/SD/HD). Under each specific regimen, half of the animals were raised in standard cages (impoverished environment (IE)) and the other half in enriched cages (enriched environment (EE)), mimicking sedentary or active lifestyles. Microscopic stereological, systematic, and random sampling approaches with an optical dissector of GFAP-immunolabeled astrocytes were done, allowing for an astrocyte numerical estimate. Stratum moleculare and hilus, from the dentate gyrus (DG) and Strata Lacunosum-Moleculare, Oriens, and Radiatum, similarly to the dentate gyrus, showed no significant change in any of the investigated variables (age, diet, or environment) in these layers. However, in Stratum radiatum, it was possible to observe significant differences associated with diet regimens and age. Therefore, diet-related differences were found when the HD 18M IE group was compared to the HD/SD/HD 18-month-old group in the same environment (IE) (p = 0.007). In the present study, we present modulatory factors (masticatory function, environmental enrichment, and aging) for the differentiated quantitative laminar response in the hippocampal regions, suggesting other studies to read the plasticity and responsiveness of astrocytes, including the molecular background