967 resultados para Typical Dessert
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"Reprinted by American society for testing materials ... from its copyrighted Proceedings, volume 30, part I, 1930."
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Published also in same series without thesis note.
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Mode of access: Internet.
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Imprint varies. No. 24-34 published: Liverpool : Liverpool University Press.
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von C.F.G. Thon
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Medullary breast cancer (MBC) is a rare, diagnostically difficult, pathological subtype. Despite being high grade, it has a good prognosis. MBC patients have an excess of BRCA1 germ-fine mutation and reliable identification of MBC could help to identify patients at risk of carrying germline BRCA1 mutations or in whom chemotherapy could be avoided. The aim of this study was therefore to improve diagnosis by establishing an MBC protein expression profile using immunohistochemistry (IHC) on tissue-microarrays (TMA). Using a series of 779 breast carcinomas ('EC' set), diagnosed initially as MBC, a double-reading session was carried out by several pathologists on all of the histological material to establish the diagnosis as firmly as possible using a 'medullary score'. Only MBCs with high scores, i.e. typical MBC (TMBC) (n = 44) and non-TMBC grade III with no or low scores (n = 160), were included in the IHC study. To validate the results obtained on this first set, a control series of TMBC (n = 17) and non-MBC grade III cases (n = 140) ('IPC' set) was studied. The expression of 18 proteins was studied in the 61 TMBCs and 300 grade III cases from the two sets. The global intra-observer concordance of the first reading for the diagnosis of TMBC was 94%, with almost perfect kappa (kappa) of 0.815. TMBC was characterized by a high degree of basal/myoepithelial differentiation. In multivariate analysis with logistic regression, TMBC was defined by the association of P-cadherin (R = 2.29), MIB1 > 50 (R = 3.80), ERBB2 negativity (R = 2.24) and p53 positivity (RR = 1.45). Copyright (c) 2005 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
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This study examined theory of mind (ToM) and concepts of human biology (eyes, heart, brain, lungs and mind) in a sample of 67 children, including 25 high functioning children with autism (age 6-13), plus age-matched and preschool comparison groups. Contrary to Baron-Cohen [1989, Journal of Autism and Developmental Disorders, 19(4), 579-600], most children with autism correctly understood the functions of the brain (84%) and the mind (64%). Their explanations were predominantly mentalistic. They outperformed typically developing preschoolers in understanding inner physiological (heart, lungs) and cognitive (brain, mind) systems, and scored as high as age-matched typical children. Yet, in line with much previous ToM research, most children with autism (60%) failed false belief, and their ToM performance was unrelated to their understanding of. human biology. Results were discussed in relation to neurobiological and social-experiential accounts of the ToM deficit in autism.
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The performance of Gallager's error-correcting code is investigated via methods of statistical physics. In this method, the transmitted codeword comprises products of the original message bits selected by two randomly-constructed sparse matrices; the number of non-zero row/column elements in these matrices constitutes a family of codes. We show that Shannon's channel capacity is saturated for many of the codes while slightly lower performance is obtained for others which may be of higher practical relevance. Decoding aspects are considered by employing the TAP approach which is identical to the commonly used belief-propagation-based decoding.
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The performance of "typical set (pairs) decoding" for ensembles of Gallager's linear code is investigated using statistical physics. In this decoding method, errors occur, either when the information transmission is corrupted by atypical noise, or when multiple typical sequences satisfy the parity check equation as provided by the received corrupted codeword. We show that the average error rate for the second type of error over a given code ensemble can be accurately evaluated using the replica method, including the sensitivity to message length. Our approach generally improves the existing analysis known in the information theory community, which was recently reintroduced in IEEE Trans. Inf. Theory 45, 399 (1999), and is believed to be the most accurate to date. © 2002 The American Physical Society.
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Typical performance of low-density parity-check (LDPC) codes over a general binary-input output-symmetric memoryless channel is investigated using methods of statistical mechanics. The binary-input additive-white-Gaussian-noise channel and the binary-input Laplace channel are considered as specific channel noise models.
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The typical behavior of the relay-without-delay channel under low-density parity-check coding and its multiple-unit generalization, termed the relay array, is studied using methods of statistical mechanics. A demodulate-and- forward strategy is analytically solved using the replica symmetric ansatz which is exact in the system studied at Nishimori's temperature. In particular, the typical level of improvement in communication performance by relaying messages is shown in the case of a small and a large number of relay units. © 2007 The American Physical Society.
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Using methods of statistical physics, we study the average number and kernel size of general sparse random matrices over GF(q), with a given connectivity profile, in the thermodynamical limit of large matrices. We introduce a mapping of GF(q) matrices onto spin systems using the representation of the cyclic group of order q as the q-th complex roots of unity. This representation facilitates the derivation of the average kernel size of random matrices using the replica approach, under the replica symmetric ansatz, resulting in saddle point equations for general connectivity distributions. Numerical solutions are then obtained for particular cases by population dynamics. Similar techniques also allow us to obtain an expression for the exact and average number of random matrices for any general connectivity profile. We present numerical results for particular distributions.