Nanostructures and adhesion in natural rubber: new era for a classic

Natural rubber is obtained from Hevea brasiliensis, a tree that is native from the Amazon forest. It has been economically important for the past 150 years and it has also been a rich source of learning on polymers and polymeric materials. Its outstanding properties and advantages over synthetic rubbers have attracted the attention of many researchers that unraveled many contributing factors. Now, it is clear that natural rubber is a complex nanostructured material formed by poly(cis-1,4-isoprene), protein, phospholipids and a host of mineral minor components. Contribution of the authors to knowledge on natural rubber is reviewed in this paper and it opened the way to develop a host of new nanocomposites, using mild, green processes, within a new paradigm for the fabrication of materials derived from renewable sources.A borracha natural é obtida da Hevea brasiliensis, uma árvore nativa da floresta amazônica. Ela tem tido grande importância econômica há mais de 150 anos, sendo uma rica fonte de aprendizagem sobre polímeros e materiais poliméricos. Suas notáveis propriedades e vantagens sobre borrachas sintéticas atraíram a atenção de muitos pesquisadores que identificaram várias singularidades estruturais. Hoje, está claro que a borracha natural é um complexo material nanoestruturado, formado por poli(cis-1,4-isopreno), proteínas, fosfolipídios e vários componentes minerais minoritários. A contribuição dos autores para esta aprendizagem está resenhada neste artigo e abriu o caminho para o desenvolvimento de novos nanocompósitos, usando processos suaves e verdes, dentro de um novo paradigma para a fabricação de materiais derivados de fontes renováveis.10241030Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES

Synthetic approaches to a challenging and unusual structure—an amino-pyrrolidine guanine core

Associate Laboratory for Green Chemistry-LAQV, which is financed by national funds from FCT/MCTES (UIDB/50006/2020). Grant number SFRH/BD/136692/2018 from FCT/MCTES.The synthesis of an unreported 2-aminopyrrolidine-1-carboxamidine unit is here described for the first time. This unusual and promising structure was attained through the oxidative decarboxylation of amino acids using the pair of reagents, silver(I)/peroxydisulfate (Ag(I)/S2O82−) followed by intermolecular (in the case of L-proline derivative) and intramolecular trapping (in the case of acyl L-arginine) by N-nucleophiles. The L-proline approach has a broader scope for the synthesis of 2-aminopyrrolidine-1-carboxamidine derivatives, whereas the intramolecular cyclization afforded by the L-acylarginines, when applied, results in higher yields. The former allowed the first synthesis of cernumidine, a natural alkaloid isolated in 2011 from Solanum cernuum Vell, as its racemic form.publishersversionpublishe

Evaluation Rainfall Regime at the Hydroelectric Power Plant Toward Climate Change

The hydroelectric plants are first in the Brazilian energy matrix, so irregularities in the rainfall regime can affect the energy generation, thus evidencing the need to know the rainfall distribution in the studied area. This work aimed to evaluate possible analysis of the impacts of climate change on the rainfall regime in the Machadinho hydroelectric region. For the research development, the IPCC-AR5 pessimistic scenario was used, representing a scenario with a continuous population growth and high carbon dioxide emissions. From the historical series and organized projections, precipitation anomalies were calculated. Analyzing the difference between the average of the month and the climatological normal, it was inferred that the model used presented a positive trend for precipitation in the period from 2026 - 2100, projecting anomalies between 25 and 200 mm per month. A greater amplitude is observed in the precipitation of 2076-2100, indicating an increase in the occurrence of extreme events of precipitation, mainly in the spring period. Considering that the rains in the Machadinho hydroelectric region are increasing in the scenarios analyzed, the average water level in the reservoir of the plant tends to increase

Extração do óleo da semente da ameixa amarela (Eriobotrya japonica)

A ameixa amarela (Eriobotrya japonica) é uma fruta cítrica de origem asiática, cultivada no sul e sudeste do Brasil. As frutas contêm de 3 a 5 sementes que são consideradas resíduos industriais e o óleo presente nestas sementes apresenta elevados níveis de polifenóis, que ajudam a combater radicais livres, podendo se tornar uma possível aplicação na área alimentícia e química. Neste sentido, este trabalho teve como objetivo avaliar diferentes condições de extração do óleo presente na semente da ameixa amarela. A fruta madura foi colhida no município de Chapecó/Santa Catarina e as sementes foram retiradas manualmente e a extração foi realizada pelo método de Soxhlet. Através de um planejamento fatorial completo 2², em duplicata, variou-se o tipo de solvente (hexano e etanol) e o tempo de extração (60 e 120 min). Os resultados mostraram que apenas o tipo de solvente foi significativo, sendo que, o solvente mais eficaz foi o etanol extraindo 15% de óleo. O modelo matemático obtido foi preditivo e explica 99,16% das respostas obtidas por ele. O solvente etanol, por ser oriundo de recursos renováveis, abre portas para futuras pesquisas na área de extração, em comparação com o solvente hexano, que pode deixar resíduos tóxicos nos óleos

Efficacy and tolerability of α-galactosidase in treating gas-related symptoms in children: a randomized, double-blind, placebo controlled trial

BACKGROUND: Gas-related symptoms represent very common complaints in children. The reduction of gas production can be considered as a valuable target in controlling symptoms. α-galactosidase has been shown to reduce gas production and related symptoms in adults. To evaluate the efficacy and tolerability of α-galactosidase in the treatment of gas-related symptoms in pediatric patients. METHODS: Single center, randomized, double-blind, placebo-controlled, parallel group study performed in tertiary care setting. Fifty-two pediatric patients (32 female, age range 4–17) with chronic or recurrent gas-related symptoms were randomized to receive placebo (n = 25) or α-galactosidase (n = 27). Both treatments were given as drops or tablets, according to body weight for 2 weeks. The primary endpoint was the reduction in global distress measured by the Faces Pain Scale-Revised (FPS-R) at the end of treatment compared to baseline. Secondary endpoints were the reduction in severity and frequency of gas-related symptoms as recorded by parents and/or children. RESULTS: α-galactosidase significantly reduced global distress (p = 0.02) compared to placebo. The digestive enzyme decreased the number of days with moderate to severe bloating (p = 0.03) and the proportion of patients with flatulence (p = 0.02). No significant differences were found for abdominal spasms and abdominal distension. No adverse events were reported during treatment. CONCLUSIONS: Although larger and longer trials are needed to confirm this result, α-galactosidase seems to be a safe, well tolerated and effective treatment for gas-related symptoms in the pediatric population. TRIAL REGISTRATION: ClinicalTrials.gov, NCT0159593

Growth and hydrolase profiles can be used as characteristics to distinguish Aspergillus niger and other black aspergilli

Wild type Aspergillus niger isolates from different biotopes from all over the world were compared to each other and to the type strains of other black Aspergillus species with respect to growth and extracellular enzyme profiles. The origin of the A. niger isolate did not result in differences in growth profile with respect to monomeric or polymeric carbon sources. Differences were observed in the growth rate of the A. niger isolates, but these were observed on all carbon sources and not specific for a particular carbon source. In contrast, carbon source specific differences were observed between the different species. Aspergillus brasiliensis is the only species able to grow on D-galactose, and A. aculeatus had significantly better growth on Locus Bean gum than the other species. Only small differences were found in the extracellular enzyme profile of the A. niger isolates during growth on wheat bran, while large differences were observed in the profiles of the different black aspergilli. In addition, differences were observed in temperature profiles between the black Aspergillus species, but not between the A. niger isolates, demonstrating no isolate-specific adaptations to the environment

The Medical Segmentation Decathlon

International challenges have become the de facto standard for comparative assessment of image analysis algorithms given a specific task. Segmentation is so far the most widely investigated medical image processing task, but the various segmentation challenges have typically been organized in isolation, such that algorithm development was driven by the need to tackle a single specific clinical problem. We hypothesized that a method capable of performing well on multiple tasks will generalize well to a previously unseen task and potentially outperform a custom-designed solution. To investigate the hypothesis, we organized the Medical Segmentation Decathlon (MSD) - a biomedical image analysis challenge, in which algorithms compete in a multitude of both tasks and modalities. The underlying data set was designed to explore the axis of difficulties typically encountered when dealing with medical images, such as small data sets, unbalanced labels, multi-site data and small objects. The MSD challenge confirmed that algorithms with a consistent good performance on a set of tasks preserved their good average performance on a different set of previously unseen tasks. Moreover, by monitoring the MSD winner for two years, we found that this algorithm continued generalizing well to a wide range of other clinical problems, further confirming our hypothesis. Three main conclusions can be drawn from this study: (1) state-of-the-art image segmentation algorithms are mature, accurate, and generalize well when retrained on unseen tasks; (2) consistent algorithmic performance across multiple tasks is a strong surrogate of algorithmic generalizability; (3) the training of accurate AI segmentation models is now commoditized to non AI experts

Risk accelerators in disasters : insights from the typhoon Haiyan response on humanitarian information management and decision support

Published version of a chapter in the book: Advanced Information Systems Engineering. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-319-07881-6_2Modern societies are increasingly threatened by disasters that require rapid response through ad-hoc collaboration among a variety of actors and organizations. The complexity within and across today's societal, economic and environmental systems defies accurate predictions and assessments of damages, humanitarian needs, and the impact of aid. Yet, decision-makers need to plan, manage and execute aid response under conditions of high uncertainty while being prepared for further disruptions and failures. This paper argues that these challenges require a paradigm shift: instead of seeking optimality and full efficiency of procedures and plans, strategies should be developed that enable an acceptable level of aid under all foreseeable eventualities. We propose a decision- and goal-oriented approach that uses scenarios to systematically explore future developments that may have a major impact on the outcome of a decision. We discuss to what extent this approach supports robust decision-making, particularly if time is short and the availability of experts is limited. We interlace our theoretical findings with insights from experienced humanitarian decision makers we interviewed during a field research trip to the Philippines in the aftermath of Typhoon Haiyan