Mokrani K, Fournier PE, Dalichaouche M, Tebbal S, Aouati A, Raoult D. Reemerging threat of epidemic typhus in Algeria. Journal of Clinical Microbiology [J Clin Microbiol], ISSN: 0095-1137, PMID: 15297561, AugJournal of Clinical Microbiology [J Clin Microbiol], ISSN: 0095-1137, PMID: 15297561, Aug. 2004;42 :pp 3898-900.Abstract
We report a case of epidemic typhus in a patient from the Batna region of Algeria, who presented with generalized febrile exanthema. The clinical diagnosis was confirmed by serological cross-adsorption followed by Western blotting. Our report emphasizes the threat of epidemic typhus in the highlands of Algeria.
Hardware fault tolerance is an important consideration in critical distributed real-time embedded systems and has been extensively researched. In these systems, critical real-time constraints must be satisfied even in the presence of hardware component failures. Our goal is to propose a solution to automatically produce a fault-tolerant distributed schedule of a given algorithm onto a given distributed architecture, according to real-time constraints. The distributed architectures we consider have bidirectional point-to-point communication links. Our solution is a list scheduling heuristics, based on disjoint paths to tolerate a fixed number of arbitrary processor and communication link failures. Because of the resource limitation in embedded systems, our heuristics implements a software solution based on the active replication technique, where each operation of the algorithm is replicated on different processors. With a detailed example, we show the techniques used to satisfy the real-time constraints and tolerate the failure of processor and communication links. Simulations show the efficiency of our method compared with other heuristics found in the literature.
Let B(H) be the C ∗-algebra of all bounded linear operators on a complex Hilbert space H, S be an invertible and selfadjoint operator in B(H) and let (I, . I ) denote a norm ideal of B(H). In this note, we shall show the following inequality: ∀X ∈ I : SXS −1 − S −1XS I (SS −1 − 1)SXS −1 + S −1XS I .
Spectrophotometric data often comprise a great number of numerical components or variables that can be used in calibration models. When a large number of such variables are incorporated into a particular model, many difficulties arise, and it is often necessary to reduce the number of spectral variables. This paper proposes an incremental (Forward–Backward) procedure, initiated using an entropy-based criterion (mutual information), to choose the first variable. The advantages of the method are discussed; results in quantitative chemical analysis by spectrophotometry show the improvements obtained with respect to traditional and nonlinear calibration models.
