Characterization of optical properties and surface roughness profiles: The Casimir force between real materials

The Lifshitz theory provides a method to calculate the Casimir force between two flat plates if the frequency dependent dielectric function of the plates is known. In reality any plate is rough and its optical properties are known only to some degree. For high precision experiments the plates must be carefully characterized otherwise the experimental result cannot be compared with the theory or with other experiments. In this chapter we explain why optical properties of interacting materials are important for the Casimir force, how they can be measured, and how one can calculate the force using these properties. The surface roughness can be characterized, for example, with the atomic force microscope images. We introduce the main characteristics of a rough surface that can be extracted from these images, and explain how one can use them to calculate the roughness correction to the force. At small separations this correction becomes large as our experiments show. Finally we discuss the distance upon contact separating two rough surfaces, and explain the importance of this parameter for determination of the absolute separation between bodies.}Comment: 33 pages, 14 figures, to appear in Springer Lecture Notes in Physics, Volume on Casimir Physics, edited by Diego Dalvit, Peter Milonni, David Roberts, and Felipe da Ros

The ASOS Surgical Risk Calculator: development and validation of a tool for identifying African surgical patients at risk of severe postoperative complications

Background: The African Surgical Outcomes Study (ASOS) showed that surgical patients in Africa have a mortality twice the global average. Existing risk assessment tools are not valid for use in this population because the pattern of risk for poor outcomes differs from high-income countries. The objective of this study was to derive and validate a simple, preoperative risk stratification tool to identify African surgical patients at risk for in-hospital postoperative mortality and severe complications. Methods: ASOS was a 7-day prospective cohort study of adult patients undergoing surgery in Africa. The ASOS Surgical Risk Calculator was constructed with a multivariable logistic regression model for the outcome of in-hospital mortality and severe postoperative complications. The following preoperative risk factors were entered into the model; age, sex, smoking status, ASA physical status, preoperative chronic comorbid conditions, indication for surgery, urgency, severity, and type of surgery. Results: The model was derived from 8799 patients from 168 African hospitals. The composite outcome of severe postoperative complications and death occurred in 423/8799 (4.8%) patients. The ASOS Surgical Risk Calculator includes the following risk factors: age, ASA physical status, indication for surgery, urgency, severity, and type of surgery. The model showed good discrimination with an area under the receiver operating characteristic curve of 0.805 and good calibration with c-statistic corrected for optimism of 0.784. Conclusions: This simple preoperative risk calculator could be used to identify high-risk surgical patients in African hospitals and facilitate increased postoperative surveillance. © 2018 British Journal of Anaesthesia. Published by Elsevier Ltd. All rights reserved.Medical Research Council of South Africa gran