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| Ramana Gopavajhula,V.; Viswanatha Chaitanya,K.; Akbar Ali Khan,P.; Shaik,Jilani P.; Narasimha Reddy,P.; Alanazi,Mohammad. |
| Superoxide dismutase (SOD, EC 1.15.1.1) is an important metal-containing antioxidant enzyme that provides the first line of defense against toxic superoxide radicals by catalyzing their dismutation to oxygen and hydrogen peroxide. SOD is classified into four metalloprotein isoforms, namely, Cu/Zn SOD, Mn SOD, Ni SOD and Fe SOD. The structural models of soybean SOD isoforms have not yet been solved. In this study, we describe structural models for soybean Cu/Zn SOD, Mn SOD and Fe SOD and provide insights into the molecular function of this metal-binding enzyme in improving tolerance to oxidative stress in plants. |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Amino acid analysis; Model evaluation; Molecular modeling; Phylogenetic analysis; Superoxide dismutase (SOD). |
| Ano: 2013 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S1415-47572013000200013 |
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| Meixner, Oliver; Pochtrager, Siegfried; Haas, Rainer. |
| Numerous companies in the Austrian food industry have already been certified in accordance with the ISO 9000 standards. However, the introduction of a quality management system in a company alone does not guarantee continuous improvement as required by the standard ÖNORM ISO 9001:2000. In order to be successful when introducing and maintaining a quality management system in a company, a number of important factors must be considered. These success factors are derived from the „European Foundation for Quality Management (EFQM) Model for Business Excellence“. The purpose of the EFQM Model is to support the internal assessment of the quality management within a company, and it can be regarded as a motor for internal improvement. In particular, for companies... |
| Tipo: Journal Article |
Palavras-chave: Quality management; Success factors; Analytic Hierarchy Process; Model evaluation; Food industry; Agribusiness. |
| Ano: 2004 |
URL: http://purl.umn.edu/97434 |
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| TOGNELLI,MARCELO F; ROIG-JUÑENT,SERGIO A; MARVALDI,ADRIANA E; FLORES,GUSTAVO E; LOBO,JORGE M. |
| Various studies have shown that model performance may vary depending on the species being modelled, the study área, or the number of sampled localities, and suggest that it is necessary to assess which model is better for a particular situation. Thus, in this study we evalúate the performance of different techniques for modelling the distribution of Patagonian insects. We applied eight of the most widely used modelling methods (artificial neural networks, BIOCLIM, classification and regression trees, DOMAIN, generalized additive models, GARP, generalized linear models, and Maxent) to the distribution of ten Patagonian insect species. We compared model performance with five accuracy measures. To overeóme the problem of not having reliable absence data with... |
| Tipo: Journal article |
Palavras-chave: Expert opinión; Model evaluation; Patagonia; Pseudo-absence data; Species distribution modelling. |
| Ano: 2009 |
URL: http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-078X2009000300003 |
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| Boschi,Raquel Stucchi; Bocca,Felipe Ferreira; Lopes-Assad,Maria Leonor Ribeiro Casimiro; Assad,Eduardo Delgado. |
| ABSTRACT: The aim of this study was to evaluate the performance of pedotransfer functions (PTFs) available in the literature to estimate soil bulk density (ρb) in different regions of Brazil, using different metrics. The predictive capacity of 25 PTFs was evaluated using the mean absolute error (MAE), mean error (ME), root mean squared error (RMSE), coefficient of determination (R2) and the regression error characteristic (REC) curve. The models performed differently when comparing observed and estimated ρb values. In general, the PTFs showed a performance close to the mean value of the bulk density data, considered as the simplest possible estimation of an attribute and used as a parameter to compare the performance of existing models (null model). The... |
| Tipo: Info:eu-repo/semantics/article |
Palavras-chave: REC curve; Model evaluation; Soil database; Tropical soil. |
| Ano: 2018 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162018000100070 |
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