262,147 research outputs found
Metabolism of archidonic acid by 5-lipoxygenase in guinea-pig lung
No full textPT: J; CR: BURKA JF, 1981, PROSTAG OTH LIPID M, V22, P683 BURKA JF, 1983, J PHARMACOL EXP THER, V225, P427 PARKER CW, 1982, BIOCHEM BIOPH RES CO, V109, P1011 SAAD MH, 1983, PROSTAGLANDINS, V25, P741 SAAD MH, 1984, EUR J PHARMACOL, V100, P13 SCHIANTARELLI P, 1981, EUR J PHARMACOL, V73, P363; NR: 6; TC: 6; J9: PROSTAGLANDINS; PG: 2; GA: TU225Source type: Electronic(1
H ? filtering for stochastic singular fuzzy systems with time-varying delay
No full textThis paper considers the H? filtering problem
for stochastic singular fuzzy systems with timevarying
delay. We assume that the state and measurement
are corrupted by stochastic uncertain exogenous
disturbance and that the system dynamic is modeled
by Ito-type stochastic differential equations. Based on
an auxiliary vector and an integral inequality, a set of
delay-dependent sufficient conditions is established,
which ensures that the filtering error system is e?t -
weighted integral input-to-state stable in mean (iISSiM).
A fuzzy filter is designed such that the filtering
error system is impulse-free, e?t -weighted iISSiM and
the H? attenuation level from disturbance to estimation
error is belowa prescribed scalar.Aset of sufficient
conditions for the solvability of the H? filtering problem
is obtained in terms of a new type of Lyapunov
function and a set of linear matrix inequalities. Simulation
examples are provided to illustrate the effectiveness
of the proposed filtering approach developed in
this paper
Optimizing Clustering Algorithms for Anti-Microbial Evaluation Data: A Majority Score-Based Evaluation of K-Means, Gaussian Mixture Model, and Multivariate T-Distribution Mixtures
No full textThis study presents a detailed analysis of the performance of the majority score clustering algorithm on three different datasets of anti-microbial evaluation, namely the minimum inhibitory concentration (MIC) of bacteria, and the antifungal activity of chemical compounds against 4 bacteria (E. coli, P. aeruginosa, S. aureus, S. pyogenes) and 2 fungi (C. albicans, As. fumigatus). Clustering is an unsupervised machine learning method used to group chemical compounds based on their similarity. In this paper, we apply the k-means clustering, Gaussian mixture model (GMM), and mixtures of multivariate t distribution to antibacterial activity datasets. To determine the optimal number of clusters and which clustering algorithm performs best, we use a variety of clustering validation indices (CVIs) which include within sum square (to be minimized), connectivity (to be minimized), Silhouette Width (to be maximized), and the Dunn Index (to be maximized). Based on the majority score clustering algorithm, we conclude that the k-means and mixture of multivariate t-distribution methods perform best in terms of the maximum CVIs, while GMM performs best in terms of the minimum CVIs. K-means clustering and mixture of multivariate t-distribution provide 3 optimal clusters for the anti-microbial evaluation of antibacterial activity dataset and 5 optimal clusters for the MIC bacteria dataset. K-means clustering, mixture of multivariate t-distribution, and GMM provide 3 optimal clusters for both the antibacterial and antifungal activity datasets. K-means clustering algorithm performs the best in terms of the majority-based clustering algorithm. This study may be useful for the pharmaceutical industry, chemists, and medical professionals in the future
Measuring industry-science links through inventor-author relations: A profiling method
No full textIn this pilot study we examine the performance of text-based profiling in recovering a set of validated inventor-author links. In a first step we match patents and publications solely based on their similarity in content. Next, we compare inventor and author names on the highest ranked matches for the occurrence of name matches. Finally, we compare these candidate matches with the names listed in a validated set of inventor-author names. Our text-based profile methodology performs significantly better than a random matching of patents and publications, suggesting that text-based profiling is a valuable complementary tool to the name searches used in previous studies.innovation; industry-science links; text-based profiling;
Mesophilic-hydrothermal-thermophilic (M-H-T) digestion of green corn straw
No full textMesophilic-hydrothermal (80-160 degrees C, 30 min)-thermophilic (M-H-T) digestion and control tests of mesophilic (M), thermophilic (T), hydrothermal-mesophilic (H-M), and mesophilic-thermophilic digestion (M-T) of green corn straw were conducted for a 20-day fermentation period. The results indicate that M-H-T is an efficient method to improve methane production. A maximum methane yield of 371.74 mL/g volatile solid was obtained by the M (3 days)-H (140 degrees C)-T (17 days) process, which was 20.44%, 16.55%, 31.44%, and 14.31% higher than the yields of the M, T, 140-M, and M-T processes. The enhanced methane production was attributed to (1) the improved hemicellulose degradation and lignin disorganization; (2) prevention of the degradation of soluble sugar, easily hydrolyzed hemicellulose and cellulose into furfural and methylfurfural; and (3) lack of formation of Maillard reaction products during initial hydrothermal treatment. (C) 2015 Elsevier Ltd. All rights reserved
A discrete and q asymptotic iteration method
No full textWe introduce a finite difference and q-difference analogues of the Asymptotic Iteration Method of Ciftci, Hall, and Saad. We give necessary, and sufficient condition for the existence of a polynomial solution to a general linear second-order difference or q-difference equation subject to a ‘terminating condition’, which is precisely defined. When a difference or q-difference equation has a polynomial solution, we show how to find the second solution.Natural Sciences and Engineering Research Council of Canad
Contribution of Information and Communication Technology (ICT) in Country’S H-Index
No full textThe aim of this study is to examine the effect of Information and Communication Technology (ICT) development on country’s scientific ranking as measured by H-index. Moreover, this study applies ICT development sub-indices including ICT Use, ICT Access and ICT skill to find the distinct effect of these sub-indices on country’s H-index. To this purpose, required data for the panel of 14 Middle East countries over the period 1995 to 2009 is collected. Findings of the current study show that ICT development increases the H-index of the sample countries. The results also indicate that ICT Use and ICT Skill sub-indices positively contribute to higher H-index but the effect of ICT access on country’s H-index is not clear
Man?sik al-H?ajj /
No full textBound with: "Mulh?q?t. S?ayd?, Mat?ba?at al-?Irf?n, 1341 [1922]"Mode of access: Internet
Heterogeneous and tissue-specific regulation of effector T cell responses by IFN-gamma during Plasmodium berghei ANKA infection.
No full textIFN-γ and T cells are both required for the development of experimental cerebral malaria during Plasmodium berghei ANKA infection. Surprisingly, however, the role of IFN-γ in shaping the effector CD4(+) and CD8(+) T cell response during this infection has not been examined in detail. To address this, we have compared the effector T cell responses in wild-type and IFN-γ(-/-) mice during P. berghei ANKA infection. The expansion of splenic CD4(+) and CD8(+) T cells during P. berghei ANKA infection was unaffected by the absence of IFN-γ, but the contraction phase of the T cell response was significantly attenuated. Splenic T cell activation and effector function were essentially normal in IFN-γ(-/-) mice; however, the migration to, and accumulation of, effector CD4(+) and CD8(+) T cells in the lung, liver, and brain was altered in IFN-γ(-/-) mice. Interestingly, activation and accumulation of T cells in various nonlymphoid organs was differently affected by lack of IFN-γ, suggesting that IFN-γ influences T cell effector function to varying levels in different anatomical locations. Importantly, control of splenic T cell numbers during P. berghei ANKA infection depended on active IFN-γ-dependent environmental signals--leading to T cell apoptosis--rather than upon intrinsic alterations in T cell programming. To our knowledge, this is the first study to fully investigate the role of IFN-γ in modulating T cell function during P. berghei ANKA infection and reveals that IFN-γ is required for efficient contraction of the pool of activated T cells
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