scholarly journals A New Automated Method and Sample Data Flow for Analysis of Volatile Nitrosamines in Human Urine

2016 ◽  
Vol 07 (02) ◽  
pp. 165-178 ◽  
Author(s):  
James A. Hodgson ◽  
Tiffany H. Seyler ◽  
Ernest McGahee ◽  
Stephen Arnstein ◽  
Lanqing Wang
2016 ◽  
Vol 40 (6) ◽  
pp. 414-418 ◽  
Author(s):  
James A. Hodgson ◽  
Tiffany H. Seyler ◽  
Lanqing Wang

Pathology ◽  
1982 ◽  
Vol 14 (2) ◽  
pp. 223
Author(s):  
A.J. Murray ◽  
C.E. Murray ◽  
F.J. Ballard ◽  
F.M. Tomas
Keyword(s):  

2018 ◽  
Vol 43 (1) ◽  
pp. 25-35 ◽  
Author(s):  
Shrila Mazumder ◽  
Rayaj A Ahamed ◽  
Ernest McGahee ◽  
Lanqing Wang ◽  
Tiffany H Seyler

1975 ◽  
Vol 35 (3-4) ◽  
pp. 193-200 ◽  
Author(s):  
Isamu Kaneko ◽  
Tsuyoshi Miura ◽  
Tatsuro Hirao ◽  
Masayuki Ikeda
Keyword(s):  

Author(s):  
J. S. Lally ◽  
R. J. Lee

In the 50 year period since the discovery of electron diffraction from crystals there has been much theoretical effort devoted to the calculation of diffracted intensities as a function of crystal thickness, orientation, and structure. However, in many applications of electron diffraction what is required is a simple identification of an unknown structure when some of the shape and orientation parameters required for intensity calculations are not known. In these circumstances an automated method is needed to solve diffraction patterns obtained near crystal zone axis directions that includes the effects of systematic absences of reflections due to lattice symmetry effects and additional reflections due to double diffraction processes.Two programs have been developed to enable relatively inexperienced microscopists to identify unknown crystals from diffraction patterns. Before indexing any given electron diffraction pattern, a set of possible crystal structures must be selected for comparison against the unknown.


Methodology ◽  
2009 ◽  
Vol 5 (1) ◽  
pp. 3-6 ◽  
Author(s):  
Merton S. Krause

There is another important artifactual contributor to the apparent improvement of persons subjected to an experimental intervention which may be mistaken for regression toward the mean. This is the phenomenon of random error and extreme selection, which does not at all involve the population regression of posttest on pretest scores but involves a quite different and independent reversion of subjects’ scores toward the population mean. These two independent threats to the internal validity of intervention evaluation studies, however, can be detected and differentiated on the sample data of such studies.


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