Time effects on textile fibers

1964 ◽  
Vol 4 (3) ◽  
pp. 208-216
Author(s):  
W. J. Hamburger
Keyword(s):  
Time Effects ◽  
Textile Fibers

Give Me Just a Little More Time: Effects of Alcohol on the Failure and Recovery of Cognitive Control

2014 ◽  
Author(s):  
Kira Bailey ◽  
Bruce D. Bartholow ◽  
J. Scott Saults ◽  
Sarah A. Lust
Keyword(s):  
Cognitive Control ◽  
Time Effects

Transit-time effects in saturated absorption resonances

1986 ◽  
Vol 47 (12) ◽  
pp. 2025-2039 ◽  
Author(s):  
A. Titov ◽  
Yu. Malyshev ◽  
Yu. Rastorguev
Keyword(s):  
Transit Time ◽  
Time Effects ◽  
Saturated Absorption

Dyeing of pet textile fibers and films in supercritical carbon dioxide

1996 ◽  
Vol 13 (3) ◽  
pp. 310-316 ◽  
Author(s):  
Ki-Hyeok Chang ◽  
Hyo-Kwang Bae ◽  
Jae-Jin Shim
Keyword(s):  
Carbon Dioxide ◽  
Supercritical Carbon Dioxide ◽  
Textile Fibers ◽  
Supercritical Carbon

scholarly journals Robust Inferences from a Before-and-After Study with Multiple Unaffected Control Groups

2013 ◽  
Vol 1 (2) ◽  
pp. 209-234 ◽  
Author(s):  
Pengyuan Wang ◽  
Mikhail Traskin ◽  
Dylan S. Small
Keyword(s):  
Sensitivity Analysis ◽  
Control Groups ◽  
Two Stage ◽  
Time Effects ◽  
Unaffected Control ◽  
Group Time ◽  
Before And After ◽  
Group Variation ◽  
The Impact ◽  
Before And After Study

AbstractThe before-and-after study with multiple unaffected control groups is widely applied to study treatment effects. The current methods usually assume that the control groups’ differences between the before and after periods, i.e. the group time effects, follow a normal distribution. However, there is usually no strong a priori evidence for the normality assumption, and there are not enough control groups to check the assumption. We propose to use a flexible skew-t distribution family to model group time effects, and consider a range of plausible skew-t distributions. Based on the skew-t distribution assumption, we propose a robust-t method to guarantee nominal significance level under a wide range of skew-t distributions, and hence make the inference robust to misspecification of the distribution of group time effects. We also propose a two-stage approach, which has lower power compared to the robust-t method, but provides an opportunity to conduct sensitivity analysis. Hence, the overall method of analysis is to use the robust-t method to test for the overall hypothesized range of shapes of group variation; if the test fails to reject, use the two-stage method to conduct a sensitivity analysis to see if there is a subset of group variation parameters for which we can be confident that there is a treatment effect. We apply the proposed methods to two datasets. One dataset is from the Current Population Survey (CPS) to study the impact of the Mariel Boatlift on Miami unemployment rates between 1979 and 1982.The other dataset contains the student enrollment and grade repeating data in West Germany in the 1960s with which we study the impact of the short school year in 1966–1967 on grade repeating rates.

PU composites based on different types of textile fibers

2021 ◽  
pp. 002199832110316
Author(s):  
Nuno Gama ◽  
B Godinho ◽  
Ana Barros-Timmons ◽  
Artur Ferreira
Keyword(s):  
Thermal Conductivity ◽  
Raw Materials ◽  
Natural Fibers ◽  
Tensile Modulus ◽  
High Water ◽  
Textile Fibers ◽  
Synthetic Fibers ◽  
Hydrophilic Nature ◽  
Different Types ◽  
Recycled Composites

In this study polyurethane (PU) residues were mixed with residues of textile fibers (cotton, wool and synthetic fibers up to 70 wt/wt) to produce 100% recycled composites. In addition, the effect of the type of fiber on the performance of the ensuing composites was evaluated. The presence of fibers showed similar effect on the density, reducing the density in the 5.5-9.0% range. In a similar manner, the addition of fillers decreased their thermal conductivity. The 70 wt/wt wool composite presented 38.1% lower thermal conductivity when compared to the neat matrix, a reduction that was similar for the other type of fibers. Moreover, the presence of fillers yields stiffer materials, especially in the case of the Wool based composites, which with 70 wt/wt of filler content increased the tensile modulus of the ensuing material 3.4 times. This was attributed to the aspect ratio and stiffness of this type of fiber. Finally, the high-water absorption and lower thermal stability observed, especially in the case of the natural fibers, was associated with the hydrophilic nature of fibers and porosity of composites. Overall, the results suggest that these textile-based composites are suitable for construction and automotive applications, with the advantage of being produced from 100% recycled raw-materials, without compromised performance.

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