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

Durabilidade de fibras naturais para geotecnia

Publicado em "Materiais de construção sustentáveis, ISSN 2183-1866, vol. 2"Estruturas fibrosas com base em fibras naturais têm ganho um espaço fundamental quando é necessário desempenhar funções de separação, drenagem, filtração, proteção e reforço, em solo. A utilização das fibras naturais torna as obras de engenharia mais sustentáveis, visto tratar-se de matérias-primas renováveis, biodegradáveis, de baixo consumo energético e não tóxicas. No presente trabalho estudou-se a influência da degradação provocada por raios ultravioleta, calor e humidade no comportamento mecânico de fibras naturais de origem vegetal usadas em geotêxteis, incluindo fibras de sisal, de banana e de coco. O estudo da durabilidade das fibras naturais incluiu ensaios de envelhecimento acelerado e ensaios em condições reais, em contacto com o solo, num período de 3 meses. Foram retiradas amostras em intervalos de 15 dias e realizados ensaios de caracterização mecânica de modo a avaliar o efeito dos parâmetros referidos. Os resultados obtidos permitem concluir que em todas as fibras estudadas se verifica uma degradação acentuada das fibras nos primeiros 15 dias. Este estudo mostra que as fibras de sisal e de banana, submetidas a degradação em solo, apresentam maior perda de resistência ao longo do tempo que as amostras submetidas a ensaios de envelhecimento acelerado em QUV. Na conceção de geotêxteis em fibra natural, é de salientar que as fibras de banana apresentam uma degradação muito acentuada tornando-as de difícil aplicação em geotecnia; as fibras de sisal e de coco apresentam características que as tornam apropriadas para desempenhar várias funções

Phenylcoumarins from Kielmeyera elata.

Friedelin, the 4-phenylcoumarins mammeisin, 4-phenyl-5-hydroxy-6-(3-methyl-1-oxobutyl)-2'-(1-hydroxy-1-methylethyl)-3 ',4 ' -dihydro(5',4 ' :7,8) furancoumarin, and mammeigin have been puri®ed from the stem of Kielmeyera elata. These compounds have previously been reported for the same species. In addition, a new derivative of mammeigin has been isolated and identi®ed as 4-phenyl-5-hydroxy-6-(3-hydroxymethyl-1-oxo-butyl)-2 ' ,2 ' -dimethyl(6 ',5 ' :7,8)pyrancoumarin

Controlling wettability of the each side of the PLA fabric through orientation of the working gases (O2 and CH4) during cold plasma treatment

This study aimed to obtain a bifunctional fabric from the point of view of hydrophilicity/hydrophobicity for biomedical applications. To achieve this, both sides of a fabric of polylactic acid (PLA) were subjected to a plasma treatment. While in a side the oxygen was introduced to the other side, simultaneously, was added methane. The plasma treatment was performed at 100 W, 1.8 mbar, during 30 minutes. By Scanning Electron Microscopy (SEM) morphological analysis, it became evident that the fabric side facing the oxygen inlet showed micropittings, while the reverse side had smooth surfaces. Analysis by X-Ray photoelectron spectroscopy (XPS) revealed an increase in the amount of oxygen in the surface of the PLA on both sides of the fabric. The surface function was characterized by measurements of water absorption rate, where it was determined that one fabric side was more hydrophilic than the other side. The results indicated achievement of a bifunctional fabric through orientation of working gases during a plasma treatment.The authors are acknowledging to financial support supplied by CAPES - Brasília/Brazil through of the CAPES/IGC program - CGCI n° 055/2010

Evaluation of a quality improvement intervention to reduce anastomotic leak following right colectomy (EAGLE): pragmatic, batched stepped-wedge, cluster-randomized trial in 64 countries

Background Anastomotic leak affects 8 per cent of patients after right colectomy with a 10-fold increased risk of postoperative death. The EAGLE study aimed to develop and test whether an international, standardized quality improvement intervention could reduce anastomotic leaks. Methods The internationally intended protocol, iteratively co-developed by a multistage Delphi process, comprised an online educational module introducing risk stratification, an intraoperative checklist, and harmonized surgical techniques. Clusters (hospital teams) were randomized to one of three arms with varied sequences of intervention/data collection by a derived stepped-wedge batch design (at least 18 hospital teams per batch). Patients were blinded to the study allocation. Low- and middle-income country enrolment was encouraged. The primary outcome (assessed by intention to treat) was anastomotic leak rate, and subgroup analyses by module completion (at least 80 per cent of surgeons, high engagement; less than 50 per cent, low engagement) were preplanned. Results A total 355 hospital teams registered, with 332 from 64 countries (39.2 per cent low and middle income) included in the final analysis. The online modules were completed by half of the surgeons (2143 of 4411). The primary analysis included 3039 of the 3268 patients recruited (206 patients had no anastomosis and 23 were lost to follow-up), with anastomotic leaks arising before and after the intervention in 10.1 and 9.6 per cent respectively (adjusted OR 0.87, 95 per cent c.i. 0.59 to 1.30; P = 0.498). The proportion of surgeons completing the educational modules was an influence: the leak rate decreased from 12.2 per cent (61 of 500) before intervention to 5.1 per cent (24 of 473) after intervention in high-engagement centres (adjusted OR 0.36, 0.20 to 0.64; P < 0.001), but this was not observed in low-engagement hospitals (8.3 per cent (59 of 714) and 13.8 per cent (61 of 443) respectively; adjusted OR 2.09, 1.31 to 3.31). Conclusion Completion of globally available digital training by engaged teams can alter anastomotic leak rates. Registration number: NCT04270721 (http://www.clinicaltrials.gov)