EFFECT OF SITE AND COMPETITION ON DIAMETER GROWTH OF Araucaria angustifolia

Although the historical interest in using the wood of Araucaria angustifolia, it is still little known concerning the factors that affect the growth. A broader understanding in this context might contribute to the development of appropriate management systems, thus increasing the productivity of plantations and, consequently, the interest in commercially using this species. The present study was based on monospecific populations established in different site conditions (Site Indices between 18-24) where individuals (n=654) were submitted to different competition levels. With the aid of multiple regression techniques, the factors that significantly affected the accumulated growth in diameter of the trees after 20 years of intervention were determined. For the set formed by all trees, 77% of the growth variation can be explained by three factors: site, the proportion of tree diameter at breast height (dbh) of the object tree for analysis in relation to the average dbh of the population before performing the clearings (Cdbh_before) and dominance status in relation to the neighboring trees (Call). The significance of the competition level before the clearing shows that late clearings have limited effects on tree growth. It is concluded that individuals are benefited for having a dominant position in relation to the neighboring trees, reaching diameters 50% larger at the end of the production cycle. Clearings that favour selected trees by removing direct competitors seem to be an interesting management strategy for the species.Keywords: Paraná-pine; Forest Management; Silviculture; Timber Production

A educação ambiental como política pública para gestão integrada dos recursos naturais: um estudo de caso do município de Paragominas no estado do Pará

Este artigo tem por objetivo analisar a educação ambiental como uma política pública implementada pelo município de Paragominas na gestão dos recursos naturais locais, como resposta à grave crise social, econômica, ecológica e cultural que aquela comunidade atravessou nas últimas décadas. Apesar de suas peculiaridades, esse município é um espaço geopolítico representativo da realidade ambiental e dos conflitos que o uso dos recursos naturais enseja na região amazônica. Sua resposta a essa crise tornou-se conhecida nacionalmente, merecedora de análise, que identificou e tipificou seus ciclos à luz das teorias sobre políticas públicas e da educação ambiental como campo de articulação entre o saber e a ética. Como resultado, são apresentados os ciclos pelos quais passaram essa política local e uma contribuição ao CONAMA (Conselho Nacional do Meio Ambiente) visando regulamentar programas de educação ambiental

Bacterial nanocellulose and long-chain fatty acids interaction: an in silico study

Chronic wounds are a big challenge in contemporary society, as they lead to a decrease in life-quality, amputations and even death. Infections and biofilm formation might occur with chronic wounds, due to the higher susceptibility to antibiotic multi-resistant bacteria. In this situation, novel wound dressing biomaterials are needed for treatment. Thus, the aim of this research was to evaluate a possible BNC interaction with tucumã oil/butter-derived fatty acids, as this system could be a promising biomaterial for wound treating. The interaction between  cellobiose (BNC basic unit) and four fatty acids was evaluated by ab initio simulations and density functional theory (DFT), through SIESTA code. Molecular docking was also used to investigate the effect of a possible releasing of the studied fatty acids to the quorum-sensing proteins of Pseudomonas aeruginosa (gram-negative bacterium) and Staphylococcus aureus (gram-positive bacterium). According to ab initio simulations, the interaction between cellobiose and fatty acids derived from tucumã oil/butter was suggested due to physical adsorption (energy around 0.17-1.33 eV) of the lipidic structures into cellobiose. A great binding affinity (∆G ranging from 4.2-8.2 kcal.mol-1) was observed for both protonated and deprotonated fatty acids against P. aeruginosa (LasI, LasA and Rhlr) and S. aureus (ArgA and ArgC) quorum-sensing proteins, indicating that these bioactive compounds might act as potential antimicrobial and/or antibiofilm agents in the proposed system. Hence, from a theoretical viewpoint, the proposed system could be a promising raw biomaterial in the production of chronic wound dressings

A Decision Support Tool for the Selection of Promoting Actions to Encourage Collaboration in Projects for the Agriculture Sector

[EN] Development and innovation agencies promote consortiums of agricultural stakeholders to collaborate in the proposal of projects for public calls. To achieve this partnerships, these agencies should select between different promoting actions to be performed with two objectives: maximize the number of project proposals presented and minimize the resources invested. To support agencies with these decisions, a computer tool based on a multi-objective integer linear programming model is proposed. To deal with the two objectives the weighting sum method is implemented. The model is validated in different scenarios by means a realistic case of an agency in Brittany (France). The results show the conflict between the two objectives considered and the dependency of the solutions on the scenarios defined. As a conclusion it can be stated that: 1) decision-makers should be careful in defining the weights of each objective and 2) the impact of the different promoting actions on the level of stakeholders¿ participation should be precisely estimated.The authors acknowledge the support of the project 691249, RUCAPS: "Enhancing and implementing knowledge based ICT solutions within high risk and uncertain conditions for agriculture production systems", funded by the European Union¿s research and innovation programme under the H2020 Marie Sk¿odowska-Curie Actions.Alemany Díaz, MDM.; Alarcón Valero, F.; Pérez Perales, D.; Guyon, C. (2020). A Decision Support Tool for the Selection of Promoting Actions to Encourage Collaboration in Projects for the Agriculture Sector. IFIP Advances in Information and Communication Technology. 598:534-545. https://doi.org/10.1007/978-3-030-62412-5_44S534545598European Comission Funded Programs. https://ec.europa.eu/programmes/horizon2020Zoie, C., Radulescu, M.: Decision analysis for the project selection problem under risk. IFAC Proc. 34(8), 445–450 (2001)Sadi-Nezhad, S.: A state-of-art survey on project selection using MCDM techniques. J. Project Manage. 2, 1–10 (2017)Caballero, H.C., Chopra, S., Schmidt, E.K.: Project portfolio selection using mathematical programming and optimization methods. In: Paper presented at PMI® Global Congress 2012–North America, Vancouver, British Columbia, Canada, Newtown Square, PA, Project Management Institute (2012)Ahmad, B., Haq, I.: Project selection techniques, relevance and applications in Pakistan. Int. J. Technol. Res. 4, 52–60 (2016)Inuiguchi, M., Ramı́k, J.: Possibilistic linear programming: a brief review of fuzzy mathematical programming and a comparison with stochastic programming in portfolio selection problem. Fuzzy Sets Syst. 111(1), 3–28 (2000)Stewart, R., Mohamed, S.: IT/IS projects selection using multi-criteria utility theory. Log. Inf. Manage. 15(4), 254–270 (2002)Alzober, W., Yaakub, A.R.: Integrated model for MCDM: selection contractor in Malaysian construction industry. In: Applied Mechanics and Materials 548, pp. 1587–1595. Trans Tech Publications (2014)Adhikary, P., Roy, P.K., Mazumdar, A.: Optimal renewable energy project selection: a multi-criteria optimization technique approach. Global J. Pure Appl. Math. 11(5), 3319–3329 (2015)Strang, K.D.: Portfolio selection methodology for a nuclear project. Project Manage. J. 42(2), 81–93 (2011)Benjamin, C.O.: A linear goal-programming model for public-sector project selection. J. Oper. Res. Soc. 36(1), 13–23 (1985)Coronado, J.R., Pardo-Mora, E.M., Valero, M.: A multi-objective model for selection of projects to finance new enterprise SMEs in Colombia. J. Ind. Eng. Manage. 4(3), 407–417 (2011)Mat, N.A.C., Cheung, Y.: Partner selection: criteria for successful collaborative network. In: 20th Australian Conference on Information Systems, pp. 631–641 (2009)Camarinha-Matos, L.M., Afsarmanesh, H.: Collaborative Networks. In: Wang, K., Kovacs, G.L., Wozny, M., Fang, M. (eds.) PROLAMAT 2006. IIFIP, vol. 207, pp. 26–40. Springer, Boston, MA (2006). https://doi.org/10.1007/0-387-34403-9_4Paixão, M., Sbragia, R., Kruglianskas, I.: Factors for selecting partners in innovation projects–evidences from alliances in the Brazilian petrochemical leader. Rev. Admin. Innov. São Paulo 11(2), 241–272 (2014)Duisters, D., Duysters, G., de Man, A.P.: The partner selection process: steps, effectiveness, governance. Ann. Hematol. 2, 7–25 (2011)Zhang, X.: Criteria for selecting the private-sector partner in public-private partnerships. J. Constr. Eng. Manage. 131(6), 631–644 (2005

LEVANTAMENTO FITOSSOCIOLÓGICO DA VEGETAÇÃO HERBÁCEA-SUBARBUSTIVA DAS DUNAS DA PRAIA DE MASSARANDUPIÓ, MUNICÍPIO DE ENTRE RIOS, BAHIA

Este estudo teve como objetivo realizar uma análise fitossociológica da composição herbácea e subarbustiva, das dunas no litoral norte da Bahia, com a finalidade de conhecer e caracterizar a comunidade do estrato herbáceo-subarbustivo. A área de estudo está localizada na praia de Massarandupió (12°19´12"S; 37°50´15"W), município de Entre Rios, Bahia. Para amostragem, foram alocadas 50 parcelas de 1m2 ao longo da área e calculados os dados fitossociológico, o índice de diversidade Shannon (H´), equabilidade de Pielou (J´) e riqueza total das espécies. Foram incluídos todos os indivíduos com hábito herbáceo e subarbustivo, sendo coletados 3.804 indivíduos, pertencentes a 12 espécies, distribuídas em nove famílias. As espécies Rhynchospora riparia, Chamaecrista ramosa, Eriocaulon sp. e Comolia ovalifolia apresentaram os maiores valores de importância (VI's). Os valores de (H') e (J') quando calculados com a cobertura vegetal foram, respectivamente, H'c = 1,453 nas/m² e J'c = 0,585. As dunas de Massarandupió apresentaram uma vegetação com ervas e subarbustos distribuídos em moitas. As famílias Fabaceae, Cyperaceae e Poaceae destacaram-se por apresentarem maior número de espécies, sendo predominantes em ambientes de praias, por se adaptarem facilmente em ambientes adversos assim como seu importante papel ecológico, auxiliando na fixação das dunas.ABSTRACTThis study aimed to carry out a phytosociological analysis of the herbaceous and sub-shrub composition of the dunes on the northern coast of Bahia, with the purpose of knowing and characterizing the herbaceous-subshrub community. The study area is located on the beach of Massarandupió (12°19 ́12"S; 37°50 ́15"W), municipality of Entre Rios, Bahia state. For sampling 50 plots of 1m 2 were allocated over the area and the phytosociological data, Shannon diversity index (H ́), Pielou equability (J ́) and total species richness were calculated. The individuals with herbaceous and sub-shrub habit were included in the present study. Were collected 3,804 individuals, belonging to 12 species, distributed in nine families. The species Rhynchospora riparia, Chamaecrista ramosa, Eriocaulon sp. and Comolia ovalifolia presentedthe highest importance values (IV's). The values of (H') and (J') when calculated with the vegetation cover were respectively, H'c = 1.453 nas/m² and J'c = 0.585. Massarandupió dunespresented vegetation with herbs and sub-shrubs distributed in thickets. The families Fabaceae, Cyperaceae and Poaceae stood out for presenting a greater number of species, being predominant in beach environments, for adapting easily in harsh environments as well as their important ecological role, assisting in the fixation of dunes.Keywords: Anthropization; herbaceous structure; Restinga; Northeast coastal vegetation

Automatic diagnosis of the 12-lead ECG using a deep neural network

The role of automatic electrocardiogram (ECG) analysis in clinical practice is limited by the accuracy of existing models. Deep Neural Networks (DNNs) are models composed of stacked transformations that learn tasks by examples. This technology has recently achieved striking success in a variety of task and there are great expectations on how it might improve clinical practice. Here we present a DNN model trained in a dataset with more than 2 million labeled exams analyzed by the Telehealth Network of Minas Gerais and collected under the scope of the CODE (Clinical Outcomes in Digital Electrocardiology) study. The DNN outperform cardiology resident medical doctors in recognizing 6 types of abnormalities in 12-lead ECG recordings, with F1 scores above 80% and specificity over 99%. These results indicate ECG analysis based on DNNs, previously studied in a single-lead setup, generalizes well to 12-lead exams, taking the technology closer to the standard clinical practice

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients

Background: Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Results: Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Conclusions: Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Figure not available: see fulltext. © 2015 Freitas et al.; licensee Springer