| 1. |
- Bader Eddin, Mohamad, et al.
(author)
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A sound insulation prediction model for floor structures in wooden buildings using neural networks approach
- 2021
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In: Proceedings of INTER-NOISE 2021 - 2021 International Congress and Exposition of Noise Control Engineering. - 0736-2935. - 9781732598652
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Conference paper (other academic/artistic)abstract
- Reliable prediction tools are yet to be developed for estimating the accurate acoustic performance of lightweight structures, which are vital especially in the design process. This paper presents a sound insulation prediction model based on artificial Neural Networks (NN) to estimate acoustic performance for airborne and impact sound insulation of floor structures. At an initial stage, the prediction model was developed and tested for a small amount of data, specifically 67 laboratory measurement curves in one third octave bands. The results indicate that the model can predict the weighted airborne reduction index Rw for various floors with a maximum error of 1 dB. The accuracy decreases with errors up to 9 dB for the weighted index for impact sound Ln,w, in cases of complex floor configurations due to large error deviations in high frequency bands between the real and estimated values. The model also shows a very good accuracy in predicting the airborne and impact sound insulation curves in the low frequencies, which are of higher interest usually in building acoustics.
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| 2. |
- Bader Eddin, Mohamad, et al.
(author)
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Prediction of Sound Insulation Using Artificial Neural Networks—Part II : Lightweight Wooden Façade Structures
- 2022
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In: Applied Sciences (Switzerland). - : MDPI AG. - 2076-3417. ; 12:14
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Journal article (peer-reviewed)abstract
- A prediction model based on artificial neural networks is adapted to forecast the acoustic performance of airborne sound insulation of various lightweight wooden façade walls. A total of 100 insulation curves were used to develop the prediction model. The data are laboratory measurements of façade walls in one-third-octave bands (50 Hz–5 kHz). For each façade wall, geometric and physical information (material type, dimensions, thicknesses, densities, and more) are used as input parameters. The model shows a satisfactory predictive capability for airborne sound reduction. A higher accuracy is obtained at middle frequencies (250 Hz–1 kHz), while lower and higher frequency ranges often show higher deviations. The weighted airborne sound reduction index ((Formula presented.)) of façades can be estimated with a maximum difference of 3 dB. Sometimes, the model shows high variations within fundamental and critical frequencies that influence the predictive precision. A sensitivity analysis is implemented to investigate the significance of parameters in insulation estimations. The material density (i.e., cross-laminated timber panel, gypsum board), thickness of the insulation materials, thickness and spacing between interior studs and the total density of façades are factors of significant weight on predictions. The results also emphasize the importance of façade thickness and the total density of the clustered exterior layers.
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| 3. |
- Blaschek, Leonard, et al.
(author)
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Different combinations of laccase paralogs nonredundantly control the amount and composition of lignin in specific cell types and cell wall layers in Arabidopsis
- 2023
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In: The Plant Cell. - : Oxford University Press (OUP). - 1040-4651 .- 1532-298X. ; 35:2, s. 889-909
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Journal article (peer-reviewed)abstract
- Vascular plants reinforce the cell walls of the different xylem cell types with lignin phenolic polymers. Distinct lignin chemistries differ between each cell wall layer and each cell type to support their specific functions. Yet the mechanisms controlling the tight spatial localization of specific lignin chemistries remain unclear. Current hypotheses focus on control by monomer biosynthesis and/or export, while cell wall polymerization is viewed as random and nonlimiting. Here, we show that combinations of multiple individual laccases (LACs) are nonredundantly and specifically required to set the lignin chemistry in different cell types and their distinct cell wall layers. We dissected the roles of Arabidopsis thaliana LAC4, 5, 10, 12, and 17 by generating quadruple and quintuple loss-of-function mutants. Loss of these LACs in different combinations led to specific changes in lignin chemistry affecting both residue ring structures and/or aliphatic tails in specific cell types and cell wall layers. Moreover, we showed that LAC-mediated lignification has distinct functions in specific cell types, waterproofing fibers, and strengthening vessels. Altogether, we propose that the spatial control of lignin chemistry depends on different combinations of LACs with nonredundant activities immobilized in specific cell types and cell wall layers.
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| 4. |
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| 5. |
- Botterweg-Paredes, Esther, et al.
(author)
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Light affects tissue patterning of the hypocotyl in the shade-avoidance response
- 2020
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In: PLOS Genetics. - : Public Library of Science (PLoS). - 1553-7390 .- 1553-7404. ; 16:3
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Journal article (peer-reviewed)abstract
- Plants have evolved strategies to avoid shade and optimize the capture of sunlight. While some species are tolerant to shade, plants such as Arabidopsis thaliana are shade-intolerant and induce elongation of their hypocotyl to outcompete neighboring plants. We report the identification of a developmental module acting downstream of shade perception controlling vascular patterning. We show that Arabidopsis plants react to shade by increasing the number and types of water-conducting tracheary elements in the vascular cylinder to maintain vascular density constant. Mutations in genes affecting vascular patterning impair the production of additional xylem and also show defects in the shade-induced hypocotyl elongation response. Comparative analysis of the shade-induced transcriptomes revealed differences between wild type and vascular patterning mutants and it appears that the latter mutants fail to induce sets of genes encoding biosynthetic and cell wall modifying enzymes. Our results thus set the stage for a deeper understanding of how growth and patterning are coordinated in a dynamic environment.
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| 6. |
- Decou, Raphaël, et al.
(author)
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Analysis of lignin composition and distribution using fluorescence laser confocal microspectroscopy
- 2017. - 1
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In: Xylem. - New York : Humana Press. - 9781493967209 - 9781493967223 ; , s. 233-247
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Book chapter (peer-reviewed)abstract
- Lignin is a polyphenolic polymer specifically accumulating in the cell walls of xylem cells in higher vascular plants. Far from being homogeneous, the lignification of xylem cell walls varies in deposition site, quantity, composition and macromolecular conformation depending on the cell wall compartment, cell type, cell developmental stage and plant species. Here, we describe how confocal microspectroscopy methods using lignin autofluorescence can be used to evaluate the relative lignin amounts, its spatial distribution and composition at the cellular and sub-cellular levels in both isolated cells and histological cross-sections of plant tissues.
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| 7. |
- Derbyshire, Paul, et al.
(author)
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Proteomic Analysis of Microtubule Interacting Proteins over the Course of Xylem Tracheary Element Formation in Arabidopsis
- 2015
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In: The Plant Cell. - : Oxford University Press (OUP). - 1040-4651 .- 1532-298X. ; 27:10, s. 2709-2726
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Journal article (peer-reviewed)abstract
- Plant vascular cells, or tracheary elements (TEs), rely on circumferential secondary cell wall thickenings to maintain sap flow. The patterns in which TE thickenings are organized vary according to the underlying microtubule bundles that guide wall deposition. To identify microtubule interacting proteins present at defined stages of TE differentiation, we exploited the synchronous differentiation of TEs in Arabidopsis thaliana suspension cultures. Quantitative proteomic analysis of microtubule pull-downs, using ratiometric N-14/N-15 labeling, revealed 605 proteins exhibiting differential accumulation during TE differentiation. Microtubule interacting proteins associated with membrane trafficking, protein synthesis, DNA/RNA binding, and signal transduction peaked during secondary cell wall formation, while proteins associated with stress peaked when approaching TE cell death. In particular, CELLULOSE SYNTHASE-INTERACTING PROTEIN1, already associated with primary wall synthesis, was enriched during secondary cell wall formation. RNAi knockdown of genes encoding several of the identified proteins showed that secondary wall formation depends on the coordinated presence of microtubule interacting proteins with nonoverlapping functions: cell wall thickness, cell wall homogeneity, and the pattern and cortical location of the wall are dependent on different proteins. Altogether, proteins linking microtubules to a range of metabolic compartments vary specifically during TE differentiation and regulate different aspects of wall patterning.
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| 8. |
- Eddin, Mohamad Bader, et al.
(author)
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A comparison of numerical approaches to quantify sound insulation of lightweight wooden floor structures
- 2022
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In: Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. - 9781906913427
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Conference paper (peer-reviewed)abstract
- Quantifying air-borne and structure-borne sound insulation is an important design consideration for the indoor comfort in a building. Although sound insulation performance is commonly measured experimentally, numerical methods can have time-saving and economic benefits. Further, numerical methods can be incorporated within building simulations to provide an estimate of the acoustic environment. In response, this paper evaluates three different computational approaches for quantifying sound insulation in one-third octave bands (50 Hz -5 kHz) of a lightweight floor including: an analytical (theoretical) model, a finite element model (FEM), and an artificial neural network (ANN) model. The three numerical methods are tested on the sound insulation of a cross laminated timber (CLT) floor. The results of this study show that the ANN model is able to accurately predict the air-borne and impact sound insulation performance at frequencies above 250 Hz, but over-predicts the air-borne performance and under-predicts the impact performance at low frequencies. However, the analytical and FEM strategies provide acceptable estimations, useful during the conceptual design stage, but with higher deviations than ANN model across all frequencies. While no model is able to accurately represent acoustic behavior across all frequencies, this work highlights the advantages and disadvantages when applied to predicting the sound insulation of a CLT floor.
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| 9. |
- Eddin, Mohamad Bader, et al.
(author)
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Prediction of Sound Insulation Using Artificial Neural Networks—Part I : LightweightWooden Floor Structures
- 2022
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In: Acoustics. - : MDPI AG. - 2624-599X. ; 4:1, s. 203-226
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Journal article (peer-reviewed)abstract
- The artificial neural networks approach is applied to estimate the acoustic performance for airborne and impact sound insulation curves of different lightweight wooden floors. The prediction model is developed based on 252 standardized laboratory measurement curves in one-third octave bands (50-5000 Hz). Physical and geometric characteristics of each floor structure (materials, thickness, density, dimensions, mass and more) are utilized as network parameters. The predictive capability is satisfactory, and the model can estimate airborne sound better than impact sound cases especially in the middle-frequency range (250-1000 Hz), while higher frequency bands often show high errors. The forecast of the weighted airborne sound reduction index Rw was calculated with a maximum error of 2 dB. However, the error increased up to 5 dB in the worse case prediction of the weighted normalized impact sound pressure level Ln,w. The model showed high variations near the fundamental and critical frequency areas which affect the accuracy. A feature attribution analysis explored the essential parameters on estimation of sound insulation. The thickness of the insulation materials, the density of cross-laminated timber slab and the concrete floating floors and the total density of floor structures seem to affect predictions the most. A comparison between wet and dry floor solution systems indicated the importance of the upper part of floors to estimate airborne and impact sound in low frequencies.
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| 10. |
- Eddin, Mohamad Bader, et al.
(author)
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Sound insulation of lightweight wooden floor structures : ANN model and sensitivity analysis
- 2022
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In: Internoise 2022 - 51st International Congress and Exposition on Noise Control Engineering. - 9781906913427
-
Conference paper (peer-reviewed)abstract
- The study aims to develop an artificial neural networks (ANN) model to estimate the acoustic performance for airborne and impact sound insulation curves of different lightweight wooden floors. The prediction model is developed using 252 standardized laboratory measurement curves in one-third octave bands (50 − 5000 Hz). Each floor structure has been divided into three parts in the database: upper, main and ceiling parts. Physical and geometric characteristics (materials, thickness, density, dimensions, mass, and more) are used as network parameters. The results demonstrated that the predictive ability of the model is satisfactory. The forecast of the weighted airborne sound reduction index Rw was calculated with a maximum error of 2 dB. However, it is increased up to 5 dB in the worst case prediction of the weighted normalized impact sound pressure level Ln,w. A sensitivity analysis explored the essential parameters on sound insulation estimation. The thickness and the density of upper and main parts of the floors seem to affect estimations the most in all frequencies. In addition, no remarkable attribution has been found for the thickness and density of the ceiling part of the structures.
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