Factors Affecting Volterra Kernel Estimation: Emphasis on Lung Tissue Viscoelasticity

10.1114/1.82 ◽  
1998 ◽  
Vol 26 (1) ◽  
pp. 103-116 ◽  
Author(s):  
Qin Zhang ◽  
Béla Suki ◽  
David T. Westwick ◽  
Kenneth R. Lutchen
Keyword(s):  
Lung Tissue ◽  
Kernel Estimation ◽  
Volterra Kernel ◽  
Factors Affecting

scholarly journals Regularized nonparametric Volterra kernel estimation

Automatica ◽  
2017 ◽  
Vol 82 ◽  
pp. 324-327 ◽  
Author(s):  
Georgios Birpoutsoukis ◽  
Anna Marconato ◽  
John Lataire ◽  
Johan Schoukens
Keyword(s):  
Kernel Estimation ◽  
Volterra Kernel

Volterra kernel estimation for mildly nonlinear amplifiers

1993 ◽  
Vol 29 (23) ◽  
pp. 2007 ◽  
Author(s):  
J.G. McRory ◽  
R. Johnston
Keyword(s):  
Kernel Estimation ◽  
Volterra Kernel ◽  
Nonlinear Amplifiers

scholarly journals Characteristics of asbestos fibers in lung tissue from occupational and environmental asbestos exposure of lung cancer patients in Busan, Korea

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hyun-Sung Jung ◽  
Eun-Kee Park ◽  
Jun-Seok Cha ◽  
Jae-Won Lee ◽  
Jong-Chun Lee ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Cancer Patients ◽  
Lung Tissue ◽  
Asbestos Exposure ◽  
Coefficient Of Determination ◽  
Factors Affecting ◽  
Lung Cancer Patients ◽  
Asbestos Fibers ◽  
Significant Difference ◽  
Occupationally Exposed

AbstractThe Asbestos Injury Relief Act in Korea requires that asbestos exposure be assessed through clinical examination and chest computed tomography (CT). However, a more specific measurement of asbestos characteristics in the lung tissue may be appropriate. We aimed to investigate the asbestos burden and characterize asbestos fibers in patients with lung cancer and ultimately assess the relationship between occupational and environmental asbestos exposure and lung cancer in Korea. We evaluated 37 lung cancer patients (LCPs) from Busan. The factors affecting asbestos burden in LCPs were analyzed using a multiple regression analysis. History of asbestos exposure (environmental/occupational), male sex, and old age were the main factors affecting asbestos burden in lung tissues of LCPs. These factors had an approximate 37% adjusted coefficient of determination. There was a significant difference in the length of asbestos fibers (4.06–37.6 µm vs. 4.26–91.7 µm) and aspect ratio (4.5–151.9 vs. 5.6–735.6) between those who were occupationally exposed to asbestos and those who were environmentally exposed (P < 0.01). Therefore, both environmental/occupational exposure to asbestos should be strongly managed to reduce the risk of lung cancer, and exposure should be assessed according to the characteristics of asbestos fibers in the lung tissue.

Lipid peroxidation during initiation of extracorporeal membrane oxygenation after hypoxia in endotoxemic rabbits

Perfusion ◽  
1999 ◽  
Vol 14 (1) ◽  
pp. 49-57 ◽  
Author(s):  
Gerhard Trittenwein ◽  
Alexandre T Rotta ◽  
Björn Gunnarsson ◽  
David M Steinhorn
Keyword(s):  
Lipid Peroxidation ◽  
Oxidative Damage ◽  
Extracorporeal Membrane Oxygenation ◽  
Pulmonary Function ◽  
G Protein ◽  
Lung Tissue ◽  
Control Group ◽  
Factors Affecting ◽  
Membrane Oxygenation ◽  
Venovenous Ecmo

Initiation of extracorporeal membrane oxygenation (ECMO) in septic children with severe respiratory failure often improves oxygenation but not pulmonary function. The factors affecting pulmonary function following onset of ECMO are not completely understood, but are thought to involve injury mediated, in part, by reactive oxygen species. We hypothesized that induction of ECMO using 100% oxygen as the sweep gas through the oxygenator would increase lipid peroxidation in endotoxin-primed animals after severe hypoxia. We further speculated that provision of oxygenated blood to the pulmonary circulation via venovenous ECMO would promote a greater degree of oxidative damage to the lung as compared to venoarterial ECMO. Eighteen New Zealand White rabbits were assigned to a control group (control) or two intervention groups subjected to 60 min of venoarterial or venovenous ECMO. ECMO was initiated following an intravenous challenge with 0.5 mg/kg of E. coli endotoxin and a period of global hypoxia leading to an arterial pH of 6.99 ± 0.09, PaCO2 of 103 ± 31 mmHg and PaO2 of 27 ± 5 mmHg. Malondialdehyde (MDA), a marker of lipid peroxidation, was measured in lung tissue homogenates and in arterial plasma. Lung tissue MDA demonstrated a strong trend towards an increase in the venoarterial group (1884 ± 945 nmol/g protein) and in the venovenous group (1905 ± 758 nmol/g protein) in comparison to the control group (644 ± 71 nmol/g protein) ( p = 0.1; significance at 95% in Scheffe test). Lung tissue MDA in the venovenous group had a significant correlation with mean PaO2 during ECMO by regression analysis ( r2 = 0.678, p = 0.044). The change in blood MDA concentration between pre-ECMO and post-ECMO values was greater in the venovenous group (pre 1.62 ± 0.61 versus post 5.12 ± 0.2.07 μmol/l, p = 0.043) compared with that seen in the venoarterial group (pre 1.46 ± 0.38 versus post 3.9 ± 0.93 μmol/l). Our data support the hypothesis that initiation of ECMO with a circuit gas oxygen concentration of 100% after global hypoxia enhances oxidative damage to lipids in endotoxin-challenged animals. During venovenous ECMO this finding is dependent on PaO2.

EM-Based Hyperparameter Optimization for Regularized Volterra Kernel Estimation

2017 ◽  
Vol 1 (2) ◽  
pp. 388-393 ◽  
Author(s):  
Jeremy G. Stoddard ◽  
James S. Welsh ◽  
Hakan Hjalmarsson
Keyword(s):  
Kernel Estimation ◽  
Volterra Kernel ◽  
Hyperparameter Optimization

scholarly journals Frequency Domain Kernel Estimation for 2nd-order Volterra Models Using Random Multi-tone Excitation

VLSI Design ◽  
2002 ◽  
Vol 15 (4) ◽  
pp. 701-713 ◽  
Author(s):  
G. Bicken ◽  
G. F. Carey ◽  
R. O. Stearman
Keyword(s):  
Frequency Domain ◽  
Semiconductor Device ◽  
Kernel Estimation ◽  
Harmonic Excitation ◽  
Volterra Kernel ◽  
Volterra Models ◽  
Output System ◽  
Gaussian Input ◽  
Kernel Estimations ◽  
Least Squares Minimization

We consider the problem of frequency domain kernel estimation using random multi-tone (harmonic) excitation for 2nd-order Volterra models. The basic approach is based on least squares minimization of model output error, and results for the Volterra kernel estimations with random multi-tone inputs and random Gaussian input are compared. We show that kernel estimation with multi-tones are very accurate and efficient compared to the latter. As an illustration, the proposed method is applied to a discrete input–output system obtained from the numerical simulation of a representative hydrodynamic system for modeling semiconductor device transport. We also consider the effect of noise in the kernel estimation.

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