conclusions vaccine based on the conjugation of p. aeruginosa pao-1 lps with dt increased anti-lps antibodies and had a significant potential to protect against pseudomonas infections. background treatment of pseudomonas aeruginosa pao-1 infections through immunological means has been proved to be efficient and protective. objectives the purpose of this study was to produce a conjugate vaccine ...

UNLABELLED A study of the use of (131)I-labeled tositumomab, preceded by an unlabeled tositumomab predose, for therapy of 76 previously untreated non-Hodgkin's lymphoma patients has been completed at the University of Michigan. Fifty-two of the 76 treated patients were imaged once during therapy with SPECT to assist in dosimetric estimation. In this article, the patient's average tumor dose, es...

in this paper, conjugate heat transfer of magneto hydrodynamic mixed convection of nanofluid about a vertical slender hollow cylinder embedded in a porous medium with high porosity have been numerically studied. the forchheimer’s modification of darcy’s law was used in representing the nanofluid motion inside the porous media. the governing boundary layer equations were transformed to non-dimen...

This tutorial describes the classic method of conjugate directions: the generalization of the conjugate-gradient method in iterative least-square inversion. I derive the algebraic equations of the conjugate-direction method from general optimization principles. The derivation explains the “magic” properties of conjugate gradients. It also justifies the use of conjugate directions in cases when ...

Conjugate gradient method is verified to be efficient for nonlinear optimization problems of large-dimension data. In this paper, a penalized linear and nonlinear combined conjugate gradient method for the reconstruction of fluorescence molecular tomography (FMT) is presented. The algorithm combines the linear conjugate gradient method and the nonlinear conjugate gradient method together based ...

This tutorial describes the classic method of conjugate directions: the generalization of the conjugate-gradient method in iterative least-square inversion. I derive the algebraic equations of the conjugate-direction method from general optimization principles. The derivation explains the “magic” properties of conjugate gradients. It also justifies the use of conjugate directions in cases when ...

Variational methods for approximate inference in machine learning often adapt a parametric probability distribution to optimize a given objective function. This view is especially useful when applying variational Bayes (VB) to models outside the conjugate-exponential family. For them, variational Bayesian expectation maximization (VB EM) algorithms are not easily available, and gradient-based m...

Conjugate gradient methods are widely used for solving large-scale unconstrained optimization problems, because they do not need the storage of matrices. In this paper, we propose a general form of three-term conjugate gradient methods which always generate a sufficient descent direction. We give a sufficient condition for the global convergence of the proposed general method. Moreover, we pres...