Modelling Amazonian forest eddy covariance data: a comparison of big leaf versus sun/shade models for the C-14 tower at Manaus I. Canopy photosynthesis

In this study, we concentrate on modelling gross primary productivity using two simple approaches to simulate canopy photosynthesis: "big leaf" and "sun/shade" models. Two approaches for calibration are used: scaling up of canopy photosynthetic parameters from the leaf to the canopy level and fitting canopy biochemistry to eddy covariance fluxes. Validation of the models is achieved by using eddy covariance data from the LBA site C14. Comparing the performance of both models we conclude that numerically (in terms of goodness of fit) and qualitatively, (in terms of residual response to different environmental variables) sun/shade does a better job. Compared to the sun/shade model, the big leaf model shows a lower goodness of fit and fails to respond to variations in the diffuse fraction, also having skewed responses to temperature and VPD. The separate treatment of sun and shade leaves in combination with the separation of the incoming light into direct beam and diffuse make sun/shade a strong modelling tool that catches more of the observed variability in canopy fluxes as measured by eddy covariance. In conclusion, the sun/shade approach is a relatively simple and effective tool for modelling photosynthetic carbon uptake that could be easily included in many terrestrial carbon models.

Suco de açaí (Euterpe oleracea Mart.): avaliação microbiológica, tratamento térmico e vida de prateleira

Um dos principais problemas enfrentados quando da elaboração do suco de açaí é a contaminação por microrganismos, oriundas de problemas técnicos e higiênico-sanitários durante o processamento. Objetivando a erradicação desta microbiota no suco de açaí foram testados os processos de pasteurização e fervura em diferentes temperaturas e tempos e avaliou-se a vida de prateleira. Os sucos foram armazenados sob congelamento a -18 ºC por 120 dias e avaliados mensalmente quanto às características microbiológicas e físico-químicas. Os resultados microbiológicos do açaí in natura demonstraram elevada contaminação por coliformes totais (> 100 NMP/ml) e fecais (> 110 NMP/ml), bolores e leveduras (> 300 UFC/ml). A pasteurização a 90ºC por cinco minutos e fervura por um minuto demonstraram eficiência na erradicação dos microrganismos, manutenção das características sensoriais e conservação do suco de açaí por 120 dias a -18 ºC.

Search for H→γγ produced in association with top quarks and constraints on the Yukawa coupling between the top quark and the Higgs boson using data taken at 7 TeV and 8 TeV with the ATLAS detector

A search is performed for Higgs bosons produced in association with top quarks using the diphoton decay mode of the Higgs boson. Selection requirements are optimized separately for leptonic and fully hadronic final states from the top quark decays. The dataset used corresponds to an integrated luminosity of 4.5 fb−1 of proton--proton collisions at a center-of-mass energy of 7 TeV and 20.3 fb−1 at 8 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. No significant excess over the background prediction is observed and upper limits are set on the tt¯H production cross section. The observed exclusion upper limit at 95% confidence level is 6.7 times the predicted Standard Model cross section value. In addition, limits are set on the strength of the Yukawa coupling between the top quark and the Higgs boson, taking into account the dependence of the tt¯H and tH cross sections as well as the H→γγ branching fraction on the Yukawa coupling. Lower and upper limits at 95% confidence level are set at −1.3 and +8.0 times the Yukawa coupling strength in the Standard Model.

Search for Higgs Boson Pair Production in the γγbb¯ Final State using pp Collision Data at s√=8TeV from the ATLAS Detector

Searches are performed for resonant and non-resonant Higgs boson pair production in the hh→γγbb¯ final state using 20 fb−1 of proton--proton collisions at a center-of-mass energy of 8TeV recorded with the ATLAS detector at the CERN Large Hadron Collider. A 95% confidence level upper limit on the cross section times branching ratio of non--resonant production is set at 2.2 pb, while the expected limit is 1.0 pb. The corresponding limit observed for a narrow resonance ranges between 0.8 and 3.5 pb as a function of its mass.

Proposta de uma máquina para colheita mecanizada de babaçu (Orbignya phalerata Mart.) para a agricultura familiar

O babaçu é uma planta de importância capital na economia de subsistência do norte do Brasil. Sua configuração sócio-ambiental o torna destaque na situação regional amazônica, onde os produtos advindos do babaçu possibilitam renda para a camada mais pobre da população amazônica, além da questão ambiental que é conotada à preservação dos babaçuais naturais. Um dos gargalos técnicos da produção do babaçu, em especial visando a extração do óleo de babaçu, é a colheita feita de forma manual e no sistema extrativista. O objetivo deste trabalho é propor o conceito de uma colhedora de babaçu moto-mecanizada, capaz de trabalhar em cultivos artificiais, assim como em florestas naturais. Foi utilizada a metodologia de projeto da matriz morfológica, onde foram elencadas as possíveis combinações de mecanismos e elementos para uma colhedora de babaçu. Como resultado foi obtido um conceito teórico, sendo concluída a viabilidade técnica de tal projeto, em estudos futuros pretende-se desenvolver estudos de viabilidade técnica detalhados, assim como estudos de viabilidade econômica.

Development of computational tools for the integrated analysis of DNA microarray data with applications in cancer research

The MAP-i Doctoral Program of the Universities of Minho, Aveiro and Porto

Morfometria das fibras das folhas de Astrocaryum murumuru var. murumuru Mart. (ARECACEAE)

A análise morfométrica das fibras das folhas de Astrocaryum murumuru var. murumuru Mart. revelou que as fibras do pecíolo apresentaram comprimento e espessura da parede superiores às regiões da ráquis e folíolo, com médias variando de 1.266,09 µm a 3.270,56 µm e 5,56 µm a 10,67 µm, respectivamente. Em relação ao índice de Runckel e coeficiente de flexibilidade, as regiões pecíolo e ráquis obtiveram valores considerados favoráveis para sua utilização na indústria papeleira e, o índice de enfeltramento demonstrou que provavelmente as fibras dessas regiões apresentarão uma boa resistência ao rasgo quando submetidas às avaliações físico-mecânicas. Diante dos resultados, a espécie se revela promissora como fonte alternativa de matéria-prima para a produção de papel, sendo necessários, entretanto, estudos de resistências físico-mecânicas a consolidação deste pré-diagnóstico.

The effects of solvent composition on the affinity of a peptide towards hair keratin: experimental and molecular dynamics data

The study of the interaction between hair filaments and formulations or peptides is of utmost importance in fields like cosmetic research. Keratin intermediate filaments structure is not fully described, limiting the molecular dynamics (MD) studies in this field although its high potential to improve the area. We developed a computational model of a truncated protofibril, simulated its behavior in alcoholic based formulations and with one peptide. The simulations showed a strong interaction between the benzyl alcohol molecules of the formulations and the model, leading to the disorganization of the keratin chains, which regress with the removal of the alcohol molecules. This behavior can explain the increase of peptide uptake in hair shafts evidenced in fluorescence microscopy pictures. The model developed is valid to computationally reproduce the interaction between hair and alcoholic formulations and provide a robust base for new MD studies about hair properties. It is shown that the MD simulations can improve hair cosmetic research, improving the uptake of a compound of interest.

Efeitos da luminosidade no crescimento de mudas de Caesalpinia ferrea Mart. ex Tul. (Leguminosae, Caesalpinoideae)

Caesalpinia ferrea é uma espécie muito utilizada como planta medicinal e na arborização e paisagismo urbano no estado do Amapá. Entretanto, informações ecofisiológicas a seu respeito são escassas. A luz é um importante fator ambiental que controla processos associados ao acúmulo de matéria seca, contribuindo assim para o crescimento vegetal. Diante disso, estudou-se o efeito de diferentes níveis de luminosidade sobre o crescimento de mudas desta espécie. Para tal, plântulas foram repicadas para sacos plásticos contendo mistura de solo e areia (2:1), sendo mantidas a pleno sol, sob sombreamento artificial com redução de 50% e 70% da luminosidade e sob sombreamento natural de um dossel fechado de floresta. O delineamento experimental foi inteiramente ao acaso, com cinco repetições. Mudas submetidas ao sombreamento natural tiveram seu crescimento fortemente inibido. A pleno sol, as mudas apresentaram maiores taxas assimilatórias líquida (TAL), menor razão parte aérea/raiz (RPAR) e menor razão de área foliar (RAF). Verificou-se pouca diferença no crescimento e alocação de biomassa entre mudas mantidas sob 50 e 70% de sombreamento, sendo que as mudas desses tratamentos atingiram valores mais altos de RPAR e RAF. Isto indica existência de plasticidade, o que reflete no aumento potencial da captura de luz, importante para manter o crescimento e a sobrevivência das mudas em baixa luminosidade. Em conjunto, os resultados mostraram ajustamento morfológico e fisiológico aos diferentes níveis de luminosidade em Caesalpinia ferrea.

Valor nutricional da polpa de açaí (Euterpe oleracea Mart) liofilizada

O Brasil é o maior produtor, consumidor e exportador da bebida açaí produzida a partir dos frutos do açaizeiro. Esta bebida ou a polpa de açaí são normalmente comercializadas a temperatura ambiente ou na forma congelada, levando à perdas nutricionais importantes. Este trabalho objetivou analisar alguns nutrientes da polpa de açaí liofilizada. Os resultados de determinações analíticas mostraram que esse produto na forma de pó é um alimento altamente calórico, 489,39 Kcal/100 g de polpa liofilizada principalmente em função dos altos conteúdos de lipídeos (40,75%), dos quais 52,70% representado pelo ácido oléico (C18:1) e 25,56% pelo palmítico (C16:0). O teor de carboidratos totais foi de 42,53% ± 3,56 e o de proteínas foi de 8,13 g ± 0,63 por 100 g de açaí liofilizado. Na avaliação do perfil de minerais foi demonstrado que o potássio (900 mg/100 g de polpa de açaí liofilizado) e o cálcio (330 mg/100 g de polpa de açaí liofilizada) foram os minerais observados em maior abundância. O magnésio também apresentou concentrações importantes (124,4 mg em 100 g de polpa liofilizada), diferente do ferro (4,5 mg em 100 g de polpa liofilizada). Diante dos resultados obtidos na avaliação da composição nutricional da polpa de açaí liofilizada, é possível concluir que esse processo pode ser considerado como uma excelente alternativa de conservação dessa polpa devido a presença de importantes componentes nutricionais encontrados na mesma.

Discrimination of Brazilian propolis according to the seasoning using chemometrics and machine learning based on UV-Vis scanning data

Propolis is a chemically complex biomass produced by honeybees (Apis mellifera) from plant resins added of salivary enzymes, beeswax, and pollen. The biological activities described for propolis were also identified for donor plants resin, but a big challenge for the standardization of the chemical composition and biological effects of propolis remains on a better understanding of the influence of seasonality on the chemical constituents of that raw material. Since propolis quality depends, among other variables, on the local flora which is strongly influenced by (a)biotic factors over the seasons, to unravel the harvest season effect on the propolis chemical profile is an issue of recognized importance. For that, fast, cheap, and robust analytical techniques seem to be the best choice for large scale quality control processes in the most demanding markets, e.g., human health applications. For that, UV-Visible (UV-Vis) scanning spectrophotometry of hydroalcoholic extracts (HE) of seventy-three propolis samples, collected over the seasons in 2014 (summer, spring, autumn, and winter) and 2015 (summer and autumn) in Southern Brazil was adopted. Further machine learning and chemometrics techniques were applied to the UV-Vis dataset aiming to gain insights as to the seasonality effect on the claimed chemical heterogeneity of propolis samples determined by changes in the flora of the geographic region under study. Descriptive and classification models were built following a chemometric approach, i.e. principal component analysis (PCA) and hierarchical clustering analysis (HCA) supported by scripts written in the R language. The UV-Vis profiles associated with chemometric analysis allowed identifying a typical pattern in propolis samples collected in the summer. Importantly, the discrimination based on PCA could be improved by using the dataset of the fingerprint region of phenolic compounds ( = 280-400m), suggesting that besides the biological activities of those secondary metabolites, they also play a relevant role for the discrimination and classification of that complex matrix through bioinformatics tools. Finally, a series of machine learning approaches, e.g., partial least square-discriminant analysis (PLS-DA), k-Nearest Neighbors (kNN), and Decision Trees showed to be complementary to PCA and HCA, allowing to obtain relevant information as to the sample discrimination.

Integrating data from heterogeneous DNA microarray platforms

DNA microarrays are one of the most used technologies for gene expression measurement. However, there are several distinct microarray platforms, from different manufacturers, each with its own measurement protocol, resulting in data that can hardly be compared or directly integrated. Data integration from multiple sources aims to improve the assertiveness of statistical tests, reducing the data dimensionality problem. The integration of heterogeneous DNA microarray platforms comprehends a set of tasks that range from the re-annotation of the features used on gene expression, to data normalization and batch effect elimination. In this work, a complete methodology for gene expression data integration and application is proposed, which comprehends a transcript-based re-annotation process and several methods for batch effect attenuation. The integrated data will be used to select the best feature set and learning algorithm for a brain tumor classification case study. The integration will consider data from heterogeneous Agilent and Affymetrix platforms, collected from public gene expression databases, such as The Cancer Genome Atlas and Gene Expression Omnibus.

Reconstructing transcriptional regulatory networks using data integration and text mining

Transcriptional Regulatory Networks (TRNs) are powerful tool for representing several interactions that occur within a cell. Recent studies have provided information to help researchers in the tasks of building and understanding these networks. One of the major sources of information to build TRNs is biomedical literature. However, due to the rapidly increasing number of scientific papers, it is quite difficult to analyse the large amount of papers that have been published about this subject. This fact has heightened the importance of Biomedical Text Mining approaches in this task. Also, owing to the lack of adequate standards, as the number of databases increases, several inconsistencies concerning gene and protein names and identifiers are common. In this work, we developed an integrated approach for the reconstruction of TRNs that retrieve the relevant information from important biological databases and insert it into a unique repository, named KREN. Also, we applied text mining techniques over this integrated repository to build TRNs. However, was necessary to create a dictionary of names and synonyms associated with these entities and also develop an approach that retrieves all the abstracts from the related scientific papers stored on PubMed, in order to create a corpora of data about genes. Furthermore, these tasks were integrated into @Note, a software system that allows to use some methods from the Biomedical Text Mining field, including an algorithms for Named Entity Recognition (NER), extraction of all relevant terms from publication abstracts, extraction relationships between biological entities (genes, proteins and transcription factors). And finally, extended this tool to allow the reconstruction Transcriptional Regulatory Networks through using scientific literature.

Search for new phenomena in the dijet mass distribution using pp collision data at s√=8 TeV with the ATLAS detector

Dijet events produced in LHC proton--proton collisions at a center-of-mass energy s√=8 TeV are studied with the ATLAS detector using the full 2012 data set, with an integrated luminosity of 20.3 fb−1. Dijet masses up to about 4.5 TeV are probed. No resonance-like features are observed in the dijet mass spectrum. Limits on the cross section times acceptance are set at the 95% credibility level for various hypotheses of new phenomena in terms of mass or energy scale, as appropriate. This analysis excludes excited quarks with a mass below 4.09 TeV, color-octet scalars with a mass below 2.72 TeV, heavy W′ bosons with a mass below 2.45 TeV, chiral W∗ bosons with a mass below 1.75 TeV, and quantum black holes with six extra space-time dimensions with threshold mass below 5.82 TeV.

Spatio-temporal modelling of environmental data

Programa Doutoral em Matemática e Aplicações.