Kirchhoff's diffraction formulaKirchhoff's diffraction formula (also called Fresnel–Kirchhoff diffraction formula) approximates light intensity and phase in optical diffraction: light fields in the boundary regions of shadows. The approximation can be used to model light propagation in a wide range of configurations, either analytically or using numerical modelling. It gives an expression for the wave disturbance when a monochromatic spherical wave is the incoming wave of a situation under consideration.
Acyanotic heart defectAn acyanotic heart defect, is a class of congenital heart defects. In these, blood is shunted (flows) from the left side of the heart to the right side of the heart, most often due to a structural defect (hole) in the interventricular septum. People often retain normal levels of oxyhemoglobin saturation in systemic circulation. This term is outdated, because a person with an acyanotic heart defect may show cyanosis (turn blue due to insufficient oxygen in the blood).
Robust regressionIn robust statistics, robust regression seeks to overcome some limitations of traditional regression analysis. A regression analysis models the relationship between one or more independent variables and a dependent variable. Standard types of regression, such as ordinary least squares, have favourable properties if their underlying assumptions are true, but can give misleading results otherwise (i.e. are not robust to assumption violations).
Multinomial logistic regressionIn statistics, multinomial logistic regression is a classification method that generalizes logistic regression to multiclass problems, i.e. with more than two possible discrete outcomes. That is, it is a model that is used to predict the probabilities of the different possible outcomes of a categorically distributed dependent variable, given a set of independent variables (which may be real-valued, binary-valued, categorical-valued, etc.).
Atrioventricular septal defectAtrioventricular septal defect (AVSD) or atrioventricular canal defect (AVCD), also known as "common atrioventricular canal" or "endocardial cushion defect" (ECD), is characterized by a deficiency of the atrioventricular septum of the heart that creates connections between all four of its chambers. It is a very specific combination of 3 defects: 1) Atrial Septal Defect (ASD), a hole in the wall between the right and left atria; 2) Ventricular Septal Defect (VSD), a hole in the wall between the right and left ventricles; and 3) Abnormalities of the mitral and/or tricuspid valves.
MaterialMaterial is a substance or mixture of substances that constitutes an object. Materials can be pure or impure, living or non-living matter. Materials can be classified on the basis of their physical and chemical properties, or on their geological origin or biological function. Materials science is the study of materials, their properties and their applications. Raw materials can be processed in different ways to influence their properties, by purification, shaping or the introduction of other materials.
Atrial septal defectAtrial septal defect (ASD) is a congenital heart defect in which blood flows between the atria (upper chambers) of the heart. Some flow is a normal condition both pre-birth and immediately post-birth via the foramen ovale; however, when this does not naturally close after birth it is referred to as a patent (open) foramen ovale (PFO). It is common in patients with a congenital atrial septal aneurysm (ASA). After PFO closure the atria normally are separated by a dividing wall, the interatrial septum.
Materials scienceMaterials science is an interdisciplinary field of researching and discovering materials. Materials engineering is an engineering field of finding uses for materials in other fields and industries. The intellectual origins of materials science stem from the Age of Enlightenment, when researchers began to use analytical thinking from chemistry, physics, and engineering to understand ancient, phenomenological observations in metallurgy and mineralogy. Materials science still incorporates elements of physics, chemistry, and engineering.
Principal component regressionIn statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). More specifically, PCR is used for estimating the unknown regression coefficients in a standard linear regression model. In PCR, instead of regressing the dependent variable on the explanatory variables directly, the principal components of the explanatory variables are used as regressors.
Composite materialA composite material (also called a composition material or shortened to composite, which is the common name) is a material which is produced from two or more constituent materials. These constituent materials have notably dissimilar chemical or physical properties and are merged to create a material with properties unlike the individual elements. Within the finished structure, the individual elements remain separate and distinct, distinguishing composites from mixtures and solid solutions.
Precession electron diffractionPrecession electron diffraction (PED) is a specialized method to collect electron diffraction patterns in a transmission electron microscope (TEM). By rotating (precessing) a tilted incident electron beam around the central axis of the microscope, a PED pattern is formed by integration over a collection of diffraction conditions. This produces a quasi-kinematical diffraction pattern that is more suitable as input into direct methods algorithms to determine the crystal structure of the sample.
General linear modelThe general linear model or general multivariate regression model is a compact way of simultaneously writing several multiple linear regression models. In that sense it is not a separate statistical linear model. The various multiple linear regression models may be compactly written as where Y is a matrix with series of multivariate measurements (each column being a set of measurements on one of the dependent variables), X is a matrix of observations on independent variables that might be a design matrix (each column being a set of observations on one of the independent variables), B is a matrix containing parameters that are usually to be estimated and U is a matrix containing errors (noise).
