Knowledge Based Modeling

Lenard, John; Pietrzyk, Marcin; Cser, L.

doi:10.1016/b978-008042701-0/50009-7

Cited by 5 publications

(2 citation statements)

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“…After training stage, SOM can rapidly make a map using the new datasets. Furthermore, having some random components based on training and identical topology it can show different results (Wehrens, 2009;Lenard et al, 1999).…”

Section: Water Quality and Eco-environmental Indices Assessmentmentioning

confidence: 99%

Potentially toxic elemental contamination in Wainivesi River, Fiji impacted by gold-mining activities using chemometric tools and SOM analysis

Kumar

Islam

Hasanuzzaman

et al. 2022

Environ Sci Pollut Res

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Potentially toxic elements (PTEs) contamination in Wainivesi River, Fiji triggered by gold-mining activities is a major public health concern deserving attention. However, chemometric approaches and pattern recognition of PTEs in surface water and sediment are yet hardly studied in Paci c Island countries like Fijin urban River. In our study, twenty-four sediment and eight water sampling sites from the Wainivesi River, Fiji were explored to evaluate the spatial pattern, eco-environmental pollution, and source apportionment of PTEs. This analysis was done using an integrated approach of self-organizing map (SOM), principle component analysis (PCA), hierarchical cluster analysis (HCA), and indexical approaches. The PTEs average concentration is decreasing order of Fe > Pb > Zn > Ni > Cr > Cu > Mn > Co > Cd for water and Fe > Zn > Pb > Mn > Cr > Ni > Cu > Co > Cd for sediment, respectively. Outcomes of eco-environmental indices including contamination and enrichment factors, and geo-accumulation index differed spatially indicated that majority of the sediment sites were highly polluted by Zn, Cd, and Ni. Cd and Ni contents can cause both ecological and human health risks. According to PCA, two sources such as point and geogenic sources for sediment and also two sources including weathering of rock-water and anthropogenic sources of PTEs for water were identi ed in the study area. The SOM analysis identi ed three spatial patterns e.g., Cr-Co-Zn-Mn, Fe-Cd and Ni-Pb-Cu in water and Zn-Cd-Cu-Mn, Cr-Ni and Fe, Co-Pb in sediment. Spatial distribution of entropy water quality index values depicted that northern and northwestern areas possess 'poor' to 'extremely-poor' quality water. The entropy weights indicated Zn, Cd and Cu as the major pollutants in deteriorating the water quality. Our nding provides a baseline database with eco-environmental and health risk measures for the Wainivesi river contamination.

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Section: Water Quality and Eco-environmental Indices Assessmentmentioning

confidence: 99%

Potentially toxic elemental contamination in Wainivesi River, Fiji impacted by gold-mining activities using chemometric tools and SOM analysis

Kumar

Islam

Hasanuzzaman

et al. 2022

Environ Sci Pollut Res

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“…Among the different types of ANNs, we used a multilayer perceptron consisting of an input, a hidden and an output layer, and a backpropagation learning algorithm (Park and Lek 2016). The latter refers to a process, where input–output pairs are presented to the network, and weights are adjusted to minimize the error between network output and actual value (Lenard et al 1999). We selected the ANNs based on the Bayesian regularisation algorithm (BRNN) (Pérez‐Rodríguez et al 2013), which prevents overfitting and usually results in a sigmoid‐shaped function, corresponding to the observed patterns of xylem and phloem formation.…”

Section: Introductionmentioning

confidence: 99%

Modelling seasonal dynamics of secondary growth in R

et al. 2022

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The monitoring of seasonal radial growth of woody plants addresses the ultimate question of when, how and why trees grow. Assessing the growth dynamics is important to quantify the effect of environmental drivers and understand how woody species will deal with the ongoing climatic changes. One of the crucial steps in the analyses of seasonal radial growth is to model the dynamics of xylem and phloem formation based on increment measurements on samples taken at relatively short intervals during the growing season. The most common approach is the use of the Gompertz equation, while other approaches, such as general additive models (GAMs) and generalised linear models (GLMs), have also been tested in recent years. For the first time, we explored artificial neural networks with Bayesian regularisation algorithm (BRNNs) and show that this method is easy to use, resistant to overfitting, tends to yield s-shaped curves and is therefore suitable for deriving temporal dynamics of secondary tree growth. We propose two data processing algorithms that allow more flexible fits. The main result of our work is the XPSgrowth() function implemented in the radial Tree Growth (rTG) R package, that can be used to evaluate and compare three modelling approaches: BRNN, GAM and the Gompertz function. The newly developed function, tested on intra-seasonal xylem and phloem formation data, has potential applications in many ecological and environmental disciplines where growth is expressed as a function of time. Different approaches were evaluated in terms of prediction error, while fitted curves were visually compared to derive their main characteristics. Our results suggest that there is no single best fitting method, therefore we recommend testing different fitting methods and selection of the optimal one.

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The core domain of retrotransposon integrase in Hordeum: predicted structure and evolution

Suoniemi¹,

Tanskanen²,

Pentikäinen³

et al. 1998

Molecular Biology and Evolution

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Propagation of long terminal repeat (LTR)-bearing retrotransposons and retroviruses requires integrase (IN, EC 2.7.7.-), encoded by the retroelements themselves, which mediates the insertion of cDNA copies back into the genome. An active retrotransposon family, BARE-1, comprises approximately 7% of the barley (Hordeum vulgare subsp. vulgare) genome. We have generated models for the secondary and tertiary structure of BARE-1 IN and demonstrate their similarity to structures for human immunodeficiency virus 1 and avian sarcoma virus INs. The IN core domains were compared for 80 clones from 28 Hordeum accessions representative of the diversity of the genus. Based on the structural model, variations in the predicted, aligned translations from these clones would have minimal structural and functional effects on the encoded enzymes. This indicates that Hordeum retrotransposon IN has been under purifying selection to maintain a structure typical of retroviral INs. These represent the first such analyses for plant INs.

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Knowledge Based Modeling

Cited by 5 publications

References 0 publications

Potentially toxic elemental contamination in Wainivesi River, Fiji impacted by gold-mining activities using chemometric tools and SOM analysis

Potentially toxic elemental contamination in Wainivesi River, Fiji impacted by gold-mining activities using chemometric tools and SOM analysis

Modelling seasonal dynamics of secondary growth in R

The core domain of retrotransposon integrase in Hordeum: predicted structure and evolution

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