Cinzas de biomassa geradas na agroindústria do cacau: caracterização e uso em substituição ao cimento

Cinza de biomassa é um resíduo sólido gerado em grande quantidade em caldeiras para produção de energia e calor. Na indústria de processamento de cacau, que usa casca de amêndoa de cacau (20%) e madeira de eucalipto (80%) como combustível, são geradas cinzas volantes e cinzas de fundo, cujas propriedades são pouco conhecidas, o que limita sua correta disposição ou aplicação. Neste trabalho, cinza fornalha (fundo) e ciclone (volante) foram coletadas, durante o processo de limpeza da caldeira, e caracterizadas quanto a composição química, morfologia (MEV), granulometria e mineralogia (DR-X) com o objetivo de avaliar a potencialidade das cinzas para uso como adição mineral. As cinzas foram beneficiadas com moagem e queima controlada a 500, 700 e 900o C. Para avaliação do efeito da cinza, foram moldadas quatro argamassas com 5% de substituição de cimento por cinza ciclone e cinza fornalha, in natura e moídas. Os resultados dos testes de absorção de água e resistência mecânica (compressão e tração na flexão) demonstraram um aumento da absorção e da porosidade para todas as misturas, mas a manutenção das propriedades mecânicas para mistura com cinza ciclone moída, quando comparada com a argamassa sem adição, demonstrando a potencialidade desta cinza como adição mineral

Regulatory T Cells Phenotype in Different Clinical Forms of Chagas' Disease

CD25High CD4+ regulatory T cells (Treg cells) have been described as key players in immune regulation, preventing infection-induced immune pathology and limiting collateral tissue damage caused by vigorous anti-parasite immune response. In this review, we summarize data obtained by the investigation of Treg cells in different clinical forms of Chagas' disease. Ex vivo immunophenotyping of whole blood, as well as after stimulation with Trypanosoma cruzi antigens, demonstrated that individuals in the indeterminate (IND) clinical form of the disease have a higher frequency of Treg cells, suggesting that an expansion of those cells could be beneficial, possibly by limiting strong cytotoxic activity and tissue damage. Additional analysis demonstrated an activated status of Treg cells based on low expression of CD62L and high expression of CD40L, CD69, and CD54 by cells from all chagasic patients after T. cruzi antigenic stimulation. Moreover, there was an increase in the frequency of the population of Foxp3+ CD25HighCD4+ cells that was also IL-10+ in the IND group, whereas in the cardiac (CARD) group, there was an increase in the percentage of Foxp3+ CD25High CD4+ cells that expressed CTLA-4. These data suggest that IL-10 produced by Treg cells is effective in controlling disease development in IND patients. However, in CARD patients, the same regulatory mechanism, mediated by IL-10 and CTLA-4 expression is unlikely to be sufficient to control the progression of the disease. These data suggest that Treg cells may play an important role in controlling the immune response in Chagas' disease and the balance between regulatory and effector T cells may be important for the progression and development of the disease. Additional detailed analysis of the mechanisms on how these cells are activated and exert their function will certainly give insights for the rational design of procedure to achieve the appropriate balance between protection and pathology during parasite infections

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

An overview of a twofold effect of crystalline admixtures in cement-based materials: From permeability-reducers to self-healing stimulators

This work presents an overview of the most relevant studies developed to understand the enhancement promoted by the double effect of the crystalline admixtures (CAs), both as permeability-reducers and as self-healing stimulators in cement-based materials. Thus, an in-depth investigation was carried out of the main mecha-nisms of CAs disclosed in the literature in order to associate the relationship between healing products and performance improvement in cementitious materials. Further, an examination of the impact of different factors in cementitious systems with CAs was reported, as well as the synergetic effects of CAs with other constituents. Finally, conclusions were drawn highlighting research needs and addressing future works in order to provide a substantial overview of the latest information in the literature for those who are working or intend to work with this type of admixture

Characterization of iron ore pellets by multimodal microscopy and image analysis

Abstract A correlative approach employing optical microscopy and scanning electron microscopy is proposed for the quantification of phases and pores in iron ore pellets. Combining mosaic images covering the full cross-sections of pellets, obtained with both techniques, it is possible to improve the discrimination of pores, quartz and silicates. First, the images must be carefully registered to show the exact same regions. The procedure for registration, discrimination and quantification was developed with Fiji open source software. A qualitative and quantitative analysis confirmed the advantages of the correlative method as compared to the individual techniques

Characterization of iron ore pellets by multimodal microscopy and image analysis

<div><p>Abstract A correlative approach employing optical microscopy and scanning electron microscopy is proposed for the quantification of phases and pores in iron ore pellets. Combining mosaic images covering the full cross-sections of pellets, obtained with both techniques, it is possible to improve the discrimination of pores, quartz and silicates. First, the images must be carefully registered to show the exact same regions. The procedure for registration, discrimination and quantification was developed with Fiji open source software. A qualitative and quantitative analysis confirmed the advantages of the correlative method as compared to the individual techniques.</p></div