84 research outputs found

    Stochastic Bounds For The Mean Characteristics Of An M/G/l Queue With General Retrial Times

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    The main goal of this paper is to investigate various monotonicity properties of a single server retrial queue with a first-come-first-served (FCFS) orbit and general retrial times using the stochastic order relations (strong stochastic (≤st), increasing convex (≤icx), and Laplace ordering (≤ L)) in order to derive performance indices bounds

    Association between Regulator of G Protein Signaling 9–2 and Body Weight

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    Regulator of G protein signaling 9–2 (RGS9–2) is a protein that is highly enriched in the striatum, a brain region that mediates motivation, movement and reward responses. We identified a naturally occurring 5 nucleotide deletion polymorphism in the human RGS9 gene and found that the mean body mass index (BMI) of individuals with the deletion was significantly higher than those without. A splicing reporter minigene assay demonstrated that the deletion had the potential to significantly decrease the levels of correctly spliced RGS9 gene product. We measured the weights of rats after virally transduced overexpression of RGS9–2 or the structurally related RGS proteins, RGS7, or RGS11, in the nucleus accumbens (NAc) and observed a reduction in body weight after overexpression of RGS9–2 but not RGS7 or 11. Conversely, we found that the RGS9 knockout mice were heavier than their wild-type littermates and had significantly higher percentages of abdominal fat. The constituent adipocytes were found to have a mean cross-sectional area that was more than double that of corresponding cells from wild-type mice. However, food intake and locomotion were not significantly different between the two strains. These studies with humans, rats and mice implicate RGS9–2 as a factor in regulating body weight.National Institute of Mental Health (U.S.) (R41MH78570 award)National Center for Research Resources (U.S.) (Rhode Island IDeA Network of Biomedical Research Excellence (RI-INBRE) Award P20RR016457-10

    Inhibitory effect of carob (Ceratonia siliqua) leaves methanolic extract on Listeria monocytogenes

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    In recent years, there has been great development in the search for new natural compounds for food preservation aimed at a partial or total replacement of currently popular antimicrobial chemicals. Carob (Ceratonia siliqua) offers a natural promising alternative for food safety and bioconservation. In this work, the methanolic extract of carob leaves (MECL) was tested for the ability to inhibit the growth of a range of microorganisms. MECL inhibited the growth of Listeria monocytogenes at 28.12 μg/mL by the broth microdilution method. The effect of this bacteriostatic concentration on the growth of this bacterium revealed a pattern of inhibition characterized by (a) a resumed growth phase, which showed a lower rate of growth if compared with controls; and (b) first a lag and then a stationary phase at a lower bacterium concentration. The study of the chemical composition of MECL by high-performance liquid chromatography and liquid chromatography/mass spectrometry showed the presence of gallic acid, (-)-epigallocatechin-3-gallate, myricitrin, isoquercitin, catechin, chlorogenic acid, and malic acid. L. monocytogenes growth inhibition was recorded for myricitrin and gallic acid at 450 μg/mL and for (-)-epigallocatechin-3-gallate and isoquercitin, respectively, at 225 and 112.5 μg/mL. Taking into account that proline is a ligand of proline dehydrogenase (PDH), the use of this compound leads us to hypothesize the mode of action of MECL constituents

    Stochastic Bounds For The Mean Characteristics Of An M/G/l Queue With General Retrial Times

    No full text
    The main goal of this paper is to investigate various monotonicity properties of a single server retrial queue with a first-come-first-served (FCFS) orbit and general retrial times using the stochastic order relations (strong stochastic (≤st), increasing convex (≤icx), and Laplace ordering (≤ L)) in order to derive performance indices bounds

    Fault‐Tolerant Prediction‐Based Scheme for Target Tracking in Wireless Sensor Networks

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    International audienceFault-tolerance is an important function in target tracking application using wireless sensor networks. We propose in this paper, an efficient fault-tolerant approach for target tracking that prevents the loss of the target. Instead of using a single prediction mechanism, our approach uses a multi-level incremental prediction technique that adjusts the prediction precision of the target movement. The responsible node of target detection uses multiple historical information pieces to calculate multi-level predictions which have different precision levels according to the number of information pieces used. Thanks to our parametric prediction model, our approach increases the prediction success rate and decreases the target loss frequency compared to basic approaches that use simple prediction models

    Routage dans les réseaux de capteurs

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