scholarly journals Macropore flow at the field scale: predictive performance of empirical models and X-ray CT analyzed macropore characteristics

2015 ◽  
Vol 12 (11) ◽  
pp. 12089-12120 ◽  
Author(s):  
M. Naveed ◽  
P. Moldrup ◽  
M. Schaap ◽  
M. Tuller ◽  
R. Kulkarni ◽  
...  
Keyword(s):  
Predictive Performance ◽  
Empirical Models ◽  
Field Scale ◽  
Soil Columns ◽  
Macropore Flow ◽  
Matric Potential ◽  
X Ray ◽  
Network Characteristics ◽  
Gas Diffusivity ◽  
Saturated Water

Abstract. Predictions of macropore flow is important for maintaining both soil and water quality as it governs key related soil processes e.g. soil erosion and subsurface transport of pollutants. However, macropore flow currently cannot be reliably predicted at the field scale because of inherently large spatial variability. The aim of this study was to perform field scale characterization of macropore flow and investigate the predictive performance of (1) current empirical models for both water and air flow, and (2) X-ray CT derived macropore network characteristics. For this purpose, 65 cylindrical soil columns (6 cm diameter and 3.5 cm height) were extracted from the topsoil (5 to 8.5 cm depth) in a 15 m × 15 m grid from an agricultural loamy field located in Silstrup, Denmark. All soil columns were scanned with an industrial CT scanner (129 μm resolution) and later used for measurements of saturated water permeability, air permeability and gas diffusivity at −30 and −100 cm matric potentials. Distribution maps for both water and air permeabilities and gas diffusivity reflected no spatial correlation irrespective of the soil texture and organic matter maps. Empirical predictive models for both water and air permeabilities showed poor performance as they were not able to realistically capture macropore flow because of poor correlations with soil texture and bulk density. The tested empirical model predicted well gas diffusivity at −100 cm matric potential, but relatively failed at −30 cm matric potential particularly for samples with biopore flow. Image segmentation output of the four employed methods was nearly the same, and matched well with measured air-filled porosity at −30 cm matric potential. Many of the CT derived macropore network characteristics were strongly interrelated. Most of the macropore network characteristics were also strongly correlated with saturated water permeability, air permeability, and gas diffusivity. The correlations between macropore network characteristics and macropore flow parameters were further improved on dividing soil samples into samples with biopore and matrix flow. Observed strong correlations between macropore network characteristics and macropore flow highlighted the need of further research on numerical simulations of macropore flow based on X-ray CT images. This could pave the way for the digital soil physics laboratory in the future.

scholarly journals Prediction of biopore- and matrix-dominated flow from X-ray CT-derived macropore network characteristics

2016 ◽  
Vol 20 (10) ◽  
pp. 4017-4030 ◽  
Author(s):  
Muhammad Naveed ◽  
Per Moldrup ◽  
Marcel G. Schaap ◽  
Markus Tuller ◽  
Ramaprasad Kulkarni ◽  
...  
Keyword(s):  
Hydraulic Conductivity ◽  
Preferential Flow ◽  
Air Permeability ◽  
Saturated Hydraulic Conductivity ◽  
Soil Columns ◽  
Macropore Flow ◽  
Matric Potential ◽  
X Ray ◽  
Network Characteristics ◽  
Gas Diffusivity

Abstract. Prediction and modeling of localized flow processes in macropores is of crucial importance for sustaining both soil and water quality. However, currently there are no reliable means to predict preferential flow due to its inherently large spatial variability. The aim of this study was to investigate the predictive performance of previously developed empirical models for both water and air flow and to explore the potential applicability of X-ray computed tomography (CT)-derived macropore network characteristics. For this purpose, 65 cylindrical soil columns (6 cm diameter and 3.5 cm height) were extracted from the topsoil (5 cm to 8.5 cm depth) in a 15 m  ×  15 m grid from an agricultural field located in Silstrup, Denmark. All soil columns were scanned with an industrial X-ray CT scanner (129 µm resolution) and later employed for measurement of saturated hydraulic conductivity, air permeability at −30 and −100 cm matric potential, and gas diffusivity at −30 and −100 cm matric potential. Distribution maps for saturated hydraulic conductivity, air permeability, and gas diffusivity reflected no autocorrelation irrespective of soil texture and organic matter content. Existing empirical predictive models for saturated hydraulic conductivity and air permeability showed poor performance, as they were not able to realistically capture macropore flow. The tested empirical model for gas diffusivity predicted measurements at −100 cm matric potential reasonably well, but failed at −30 cm matric potential, particularly for soil columns with biopore-dominated flow. X-ray CT-derived macroporosity matched the measured air-filled porosity at −30 cm matric potential well. Many of the CT-derived macropore network characteristics were strongly interrelated. Most of the macropore network characteristics were also significantly correlated with saturated hydraulic conductivity, air permeability, and gas diffusivity. The predictive Ahuja et al. (1984) model for saturated hydraulic conductivity, air permeability, and gas diffusivity performed reasonably well when parameterized with novel, X-ray CT-derived parameters such as effective percolating macroporosity for biopore-dominated flow and total macroporosity for matrix-dominated flow. The obtained results further indicate that it is crucially important to discern between matrix-dominated and biopore-dominated flow for accurate prediction of macropore flow from X-ray CT-derived macropore network characteristics.

A robust framework for shoulder implant X-ray image classification

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Minh Thanh Vo ◽  
Anh H. Vo ◽  
Tuong Le
Keyword(s):  
Image Classification ◽  
Performance Metrics ◽  
State Of The Art ◽  
Area Under The Curve ◽  
Predictive Performance ◽  
Extraction Process ◽  
Content Type ◽  
X Ray ◽  
Robust Model ◽  
Input Dataset

PurposeMedical images are increasingly popular; therefore, the analysis of these images based on deep learning helps diagnose diseases become more and more essential and necessary. Recently, the shoulder implant X-ray image classification (SIXIC) dataset that includes X-ray images of implanted shoulder prostheses produced by four manufacturers was released. The implant's model detection helps to select the correct equipment and procedures in the upcoming surgery.Design/methodology/approachThis study proposes a robust model named X-Net to improve the predictability for shoulder implants X-ray image classification in the SIXIC dataset. The X-Net model utilizes the Squeeze and Excitation (SE) block integrated into Residual Network (ResNet) module. The SE module aims to weigh each feature map extracted from ResNet, which aids in improving the performance. The feature extraction process of X-Net model is performed by both modules: ResNet and SE modules. The final feature is obtained by incorporating the extracted features from the above steps, which brings more important characteristics of X-ray images in the input dataset. Next, X-Net uses this fine-grained feature to classify the input images into four classes (Cofield, Depuy, Zimmer and Tornier) in the SIXIC dataset.FindingsExperiments are conducted to show the proposed approach's effectiveness compared with other state-of-the-art methods for SIXIC. The experimental results indicate that the approach outperforms the various experimental methods in terms of several performance metrics. In addition, the proposed approach provides the new state of the art results in all performance metrics, such as accuracy, precision, recall, F1-score and area under the curve (AUC), for the experimental dataset.Originality/valueThe proposed method with high predictive performance can be used to assist in the treatment of injured shoulder joints.

scholarly journals Saturated water conductivity estimation based on X-ray CT images – evaluation of the impact of thresholding errors

2019 ◽  
Vol 33 (1) ◽  
pp. 49-60 ◽  
Author(s):  
Bartłomiej Gackiewicz ◽  
Krzysztof Lamorski ◽  
Cezary Sławiński
Keyword(s):  
Ct Images ◽  
Water Conductivity ◽  
X Ray ◽  
Saturated Water ◽  
The Impact

Electrocatalytic reduction of oxygen with phenanthroline-strapped porphyrins

2007 ◽  
Vol 11 (04) ◽  
pp. 212-221 ◽  
Author(s):  
Frédéric Melin ◽  
Corinne Boudon ◽  
Mamadou Lo ◽  
Kurt J. Schenk ◽  
Michel Bonin ◽  
...  
Keyword(s):  
Pyrolytic Graphite ◽  
Iron Complex ◽  
Electrocatalytic Reduction ◽  
X Ray Diffraction ◽  
X Ray ◽  
Alkyl Chains ◽  
Saturated Water ◽  
Electron Reduction ◽  
Disk Electrodes ◽  
Parent Ligand

The electrochemical behavior of three cytochrome c oxidase models has been investigated. All the models are derived from a phenanthroline-strapped, porphyrin framework that binds zinc(II) or iron(III) chloride in the porphyrin subunit, and copper(I) in the phenanthroline site. The iron complex and the bimetallic zinc(II) copper(I) complex of the parent ligand have been characterized by X-ray diffraction. One model consists of the parent structure on which C 12 alkyl chains have been added. This soluble model achieves electrochemical 2-electron reduction of oxygen in organic solvents without the addition of an exogenous axial base, and in the presence of an organic or inorganic source of protons. The two other models comprise the parent phenanthroline-strapped porphyrin framework, on which two pendant imidazoles have been incorporated. These models adsorbed on ring-disk electrodes with an edge-oriented, pyrolytic graphite (EOPG) disk and a platinum ring, efficiently catalyze the 4-electron reduction of oxygen in dioxygen saturated water at neutral pH.

scholarly journals Convolutional Support Vector Models: Prediction of Coronavirus Disease Using Chest X-rays

Information ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 548
Author(s):  
Mateus Maia ◽  
Jonatha S. Pimentel ◽  
Ivalbert S. Pereira ◽  
João Gondim ◽  
Marcos E. Barreto ◽  
...  
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Predictive Performance ◽  
Polynomial Kernel ◽  
Support Vector ◽  
X Rays ◽  
X Ray ◽  
Applied Study ◽  
The World ◽  
Simulated Images

The disease caused by the new coronavirus (COVID-19) has been plaguing the world for months and the number of cases are growing more rapidly as the days go by. Therefore, finding a way to identify who has the causative virus is impressive, in order to find a way to stop its proliferation. In this paper, a complete and applied study of convolutional support machines will be presented to classify patients infected with COVID-19 using X-ray data and comparing them with traditional convolutional neural network (CNN). Based on the fitted models, it was possible to observe that the convolutional support vector machine with the polynomial kernel (CSVMPol) has a better predictive performance. In addition to the results obtained based on real images, the behavior of the models studied was observed through simulated images, where it was possible to observe the advantages of support vector machine (SVM) models.

An X-ray diffraction system with controlled relative humidity and temperature

1996 ◽  
Vol 11 (4) ◽  
pp. 288-289 ◽  
Author(s):  
H. Hashizume ◽  
S. Shimomura ◽  
H. Yamada ◽  
T. Fujita ◽  
H. Nakazawa ◽  
...  
Keyword(s):  
Relative Humidity ◽  
Room Temperature ◽  
Control Unit ◽  
Saturated Water Vapor ◽  
X Ray Diffraction ◽  
X Ray ◽  
Saturated Water ◽  
Sample Chamber ◽  
Diffraction Patterns ◽  
Xrd Patterns

A system enabling X-ray diffraction patterns under controlled conditions of relative humidity and temperature has been devised and combined with an X-ray powder diffractometer. Relative humidity in the sample space is controlled by mixing dry N2 gas with saturated water vapor. Temperatures of the sample and inner wall of the sample chamber are monitored by two attached thermocouples and the information was fed back to the control unit. Relative humidity between 0% and the 95%, and temperature between room temperature and 60 °C can be controlled. All parameters including those for XRD are programmable and the system runs automatically. The function of the system was checked by recording the XRD patterns of montmorillonite (a clay mineral) and NaCl under increasing and decreasing relative humidity.

X-ray scattering of calcite thin films deposited by atomic layer deposition: Studies in air and in calcite saturated water solution

2014 ◽  
Vol 565 ◽  
pp. 277-284 ◽  
Author(s):  
Peng Wang ◽  
Michael R. Hudak ◽  
Allan Lerner ◽  
Robert K. Grubbs ◽  
Shanmin Wang ◽  
...  
Keyword(s):  
Thin Films ◽  
Atomic Layer Deposition ◽  
Water Solution ◽  
Atomic Layer ◽  
X Ray ◽  
X Ray Scattering ◽  
Saturated Water ◽  
Layer Deposition ◽  
Saturated Water Solution ◽  
Ray Scattering

Respiratory gas diffusivity mapping of horticultural product using X-ray CT

2021 ◽  
pp. 281-288
Author(s):  
B. Nugraha ◽  
P. Verboven ◽  
S. Janssen ◽  
B.M. Nicolaï
Keyword(s):  
X Ray ◽  
Gas Diffusivity

scholarly journals Averaged water potentials in soil water and groundwater, and their connection to menisci in soil pores, field-scale flow phenomena, and simple groundwater flows

2011 ◽  
Vol 15 (5) ◽  
pp. 1601-1614 ◽  
Author(s):  
G. H. de Rooij
Keyword(s):  
Potential Energy ◽  
Scale Effects ◽  
Hydrostatic Equilibrium ◽  
Subsurface Water ◽  
Depth Range ◽  
Pore Scale ◽  
Field Scale ◽  
Matric Potential ◽  
Water Potentials ◽  
Soil Pores

Abstract. The movement of subsurface water is mostly studied at the pore scale and the Darcian scale, but the field and regional scales are of much larger societal interest. Volume-averaging has provided equations at these larger scales, but the required restrictions rendered them of little practical interest. Others hypothesized a direct connection at hydrostatic equilibrium between the average matric potential of a subsurface body of water and the average pressure drop over the menisci in the soil pores. The link between the volume-averaged potential energy of subsurface water bodies and large-scale fluxes remains largely unexplored. This paper treats the effect of menisci on the potential energy of the water behind them in some detail, and discusses some field-scale effects of pore-scale processes. Then, various published expressions for volume-averaged subsurface water potentials are compared. The intrinsic phase average is deemed the best choice. The hypothesized relationship between average matric potential and average meniscus curvature is found to be valid for unit gradient flow instead of hydrostatic equilibrium. Still, this restriction makes the relationship hold only for a specific depth range in the unsaturated zone under specific conditions, and certainly not for entire fields or catchments. In the groundwater, volume-averaged potential energy is of more use: for linearized, steady flows with flow lines that are parallel, radially diverging, and radially converging, proofs are derived for proportionality between averaged hydraulic potentials and fluxes towards open water at a fixed potential. For parallel flow, a simplified but relevant transient flow case also exhibits this proportionality.

Study of the Hydration Process of Synthetic Preparation of Ettringite by Direct Addition of Aluminum Sulfate and Calcium Hydroxide

2018 ◽  
Vol 276 ◽  
pp. 60-65
Author(s):  
Marcela Fridrichová ◽  
Dominik Gazdič ◽  
Jana Mokrá ◽  
Karel Dvořák
Keyword(s):  
Calcium Hydroxide ◽  
Aluminum Sulfate ◽  
Xrd Analysis ◽  
Standard Laboratory ◽  
X Ray Diffraction ◽  
X Ray ◽  
Saturated Water ◽  
Direct Addition ◽  
Different Temperatures ◽  
The Stability

The stability of ettringite as high-watery mineral is highly dependent on the ambient temperature. Under standard laboratory conditions, onset of decomposition of this phase occurs at temperature of 80°C already and the theoretical temperature of the complete decomposition of ettringite is 180°C. Ettringite decomposition can occur at significantly different temperatures under humidity conditions other than the laboratory ones. Within the work verification of the possibility of synthetic preparation of ettringite by direct addition of aluminum sulfate, Al2(SO4)3·18H2O, and calcium hydroxide, Ca (OH)2, as an alternative method to the yeelimite hydration procedure was carried out. The stability of the resulting systems was examined in two different environments, namely in a laboratory environment and the environment of saturated water vapour. The phase composition of the samples was determined by X-ray diffraction (XRD) analysis, thermal analysis and scanning electron microscopy (SEM).

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