Behavioural response of farmed Atlantic salmon (Salmo salar L.) to artificial underwater lights : Wavelet analysis of acoustic telemetry data

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Evaluating different machine learning methods to simulate runoff from extensive green roofs

Green roofs are increasingly popular measures to permanently reduce or delay storm-water runoff. The main objective of the study was to examine the potential of using machine learning (ML) to simulate runoff from green roofs to estimate their hydrological performance. Four machine learning methods, artificial neural network (ANN), M5 model tree, long short-term memory (LSTM) and k nearest neighbour (kNN), were applied to simulate storm-water runoff from 16 extensive green roofs located in four Norwegian cities across different climatic zones. The potential of these ML methods for estimating green roof retention was assessed by comparing their simulations with a proven conceptual retention model. Furthermore, the transferability of ML models between the different green roofs in the study was tested to investigate the potential of using ML models as a tool for planning and design purposes. The ML models yielded low volumetric errors that were comparable with the conceptual retention models, which indicates good performance in estimating annual retention. The ML models yielded satisfactory modelling results (NSE >0.5) in most of the roofs, which indicates an ability to estimate green roof detention. The variations in ML models' performance between the cities was larger than between the different configurations, which was attributed to the different climatic characteristics between the four cities. Transferred ML models between cities with similar rainfall events characteristics (Bergen–Sandnes, Trondheim–Oslo) could yield satisfactory modelling performance (Nash–Sutcliffe efficiency NSE >0.5 and percentage bias |PBIAS| <25 %) in most cases. However, we recommend the use of the conceptual retention model over the transferred ML models, to estimate the retention of new green roofs, as it gives more accurate volume estimates. Follow-up studies are needed to explore the potential of ML models in estimating detention from higher temporal resolution datasets

Changes in microstructure and stiffness of Scots pine (Pinus sylvestrisL) sapwood degraded by Gloeophyllum trabeum and Trametes versicolor – Part II: anisotropic stiffness properties

Fungal decay considerably affects the macroscopic mechanical properties of wood as a result of modifications and degradations in its microscopic structure. While effects on mechanical properties related to the stem direction are fairly well understood, effects on radial and tangential directions (transverse properties) are less well investigated. In the present study, changes of longitudinal elastic moduli and stiffness data in all anatomical directions of Scots pine (Pinus sylvestris) sapwood which was degraded by Gloeophyllum trabeum (brown rot) and Trametes versicolor (white rot) for up to 28 weeks have been investigated. Transverse properties were found to be much more deteriorated than the longitudinal ones. This is because of the degradation of the polymer matrix between the cellulose microfibrils, which has a strong effect on transverse stiffness. Longitudinal stiffness, on the other hand, is mainly governed by cellulose microfibrils, which are more stable agains fungal decay. G. trabeum (more active in earlywood) strongly weakens radial stiffness, whereas T. versicolor (more active in latewood) strongly reduces tangential stiffness. The data in terms of radial and tangential stiffnesses, as well as the corresponding anisotropy ratios, seem to be suitable as durability indicators of wood and even allow conclusions to be made on the degradation mechanisms of fungi

Fungal and termite resistance of wood treated with 4-methoxytrityl tetrafluoroborate

This study evaluates the decay and termite resistance of Scots pine (Pinus sylvestris L.) treated with 4-methoxytrityl tetrafluoroborate (MTFB). Decay resistance tests of unleached samples showed that 2%, 1.5% and 1% concentrations of MTFB (15.4 kg/m(3), 11.1 kg/m(3), and 7.4 kg/m(3), retention levels, respectively) gave less than 2% decay of Postia placenta and concentrations of 2% and 1.5% less than 2% decay of Coniophora puteana. Wood specimens treated with 4-methoxytrityl tetrafluoroborate solutions were not protected against the brown rot fungi after a 14-day severe leaching process, suggesting excessive leaching of the chemical from wood. Treatment with 2% concentration protected against subterranean termites, Coptotermes formosanus Shiraki based on mass losses in both leached and unleached wood specimens in comparison with lower concentration levels. These results suggest that 4-methoxytrityl tetrafluoroborate might be promising to protect wood being used outdoors against termite attack. However, 4-methoxytrityl tetrafluoroborate did not protect wood against fungal decay. Field tests are needed to observe the performance of 4-methoxytrityl tetrafluoroborate treated wood in ground contact

Thermogravimetric analysis for wood decay characterisation

The paper focuses on the use of thermogravimetric analysis (TGA) as a fast method for estimating the change of lignocellulosic materials during fungal degradation in laboratory trials. Traditionally, evaluations of durability tests are based on mass loss. However, to gain more knowledge of the reasons for differences in durability and strength between wooden materials, information on the chemical changes is needed. Pinus sylvestris sapwood was incubated with the brown rot fungus Gloeophyllum trabeum and the white rot fungus Trametes versicolor. The TGA approach used was found to be reproducible between laboratories. The TGA method did not prove useful for wood deteriorated by white rot, but the TGA showed to be a convenient tool for fast estimation of lignocellulosic components both in sound wood and wood decayed by brown rot

Microstructure and stiffness of Scots pine (Pinus sylvestris L) sapwood degraded by Gloeophyllum trabeum and Trametes versicolor – Part I: changes in chemical composition, density and equilibrium moisture content

Fungal degradation alters the microstructure of wood and its physical and chemical properties are also changed. While these changes are well investigated as a function of mass loss, mass density loss and changes in equilibrium moisture content are not well elucidated. The physical and chemical alterations are crucial when linking microstructural characteristics with macroscopic mechanical properties. In the present article, a consistent set of physical, chemical and mechanical characteristics is presented, which were measured on the same sample before and after fungal degradation. In the first part of this two-part contribution, elucidating microstructure/stiffness-relationships of degraded wood, changes in physical and chemical data are presented, which were collected from specimens of Scots pine (Pinus sylvestris) sapwood degraded by Gloeophyllum trabeum (brown rot) and Trametes versicolor (white rot) for up to 28 weeks degradation time. A comparison of mass loss with corresponding mass density loss demonstrated that mass loss entails two effects: firstly, a decrease in sample size (more pronounced for G. trabeum), and secondly, a decrease of mass density within the sample (more pronounced for T. versicolor). These two concurrent effects are interrelated with sample size and shape. Hemicelluloses and cellulose are degraded by G. trabeum, while T. versicolor was additionally able to degrade lignin. In particular because of the breakdown of hemicelluloses and paracrystalline parts of cellulose, the equilibrium moisture content of degraded samples is lower than that in the initial state