Viscous vortex flows

Several computational studies are currently being pursued that focus on various aspects of representing the entire lifetime of the viscous trailing vortex wakes generated by an aircraft. The formulation and subsequent near-wing development of the leading-edge vortices formed by a delta wing are being calculated at modest Reynolds numbers using a three-dimensional, time-dependent Navier-Stokes code. Another computational code was developed to focus on the roll-up, trajectory, and mutual interaction of trailing vortices further downstream from the wing using a two-dimensional, time-dependent, Navier-Stokes algorithm. To investigate the effect of a cross-wind ground shear flow on the drift and decay of the far-field trailing vortices, a code was developed that employs Euler equations along with matched asymptotic solutions for the decaying vortex filaments. And finally, to simulate the conditions far down stream after the onset of the Crow instability in the vortex wake, a full three-dimensional, time-dependent Navier-Stokes code was developed to study the behavior of interacting vortex rings

Autophagy: A cyto-protective mechanism which prevents primary human hepatocyte apoptosis during oxidative stress

The role of autophagy in the response of human hepatocytes to oxidative stress remains unknown. Understanding this process may have important implications for the understanding of basic liver epithelial cell biology and the responses of hepatocytes during liver disease. To address this we isolated primary hepatocytes from human liver tissue and exposed them ex vivo to hypoxia and hypoxia-reoxygenation (H-R). We showed that oxidative stress increased hepatocyte autophagy in a reactive oxygen species (ROS) and class III PtdIns3K-dependent manner. Specifically, mitochondrial ROS and NADPH oxidase were found to be key regulators of autophagy. Autophagy involved the upregulation of BECN1, LC3A, Atg7, Atg5 and Atg 12 during hypoxia and H-R. Autophagy was seen to occur within the mitochondria of the hepatocyte and inhibition of autophagy resulted in the lowering a mitochondrial membrane potential and onset of cell death. Autophagic responses were primarily observed in the large peri-venular (PV) hepatocyte subpopulation. Inhibition of autophagy, using 3-methyladenine, increased apoptosis during H-R. Specifically, PV human hepatocytes were more susceptible to apoptosis after inhibition of autophagy. These findings show for the first time that during oxidative stress autophagy serves as a cell survival mechanism for primary human hepatocytes

A 3-dimensional in vitro model of epithelioid granulomas induced by high aspect ratio nanomaterials

<p>Abstract</p> <p>Background</p> <p>The most common causes of granulomatous inflammation are persistent pathogens and poorly-degradable irritating materials. A characteristic pathological reaction to intratracheal instillation, pharyngeal aspiration, or inhalation of carbon nanotubes is formation of epithelioid granulomas accompanied by interstitial fibrosis in the lungs. In the mesothelium, a similar response is induced by high aspect ratio nanomaterials, including asbestos fibers, following intraperitoneal injection. This asbestos-like behaviour of some engineered nanomaterials is a concern for their potential adverse health effects in the lungs and mesothelium. We hypothesize that high aspect ratio nanomaterials will induce epithelioid granulomas in nonadherent macrophages in 3D cultures.</p> <p>Results</p> <p>Carbon black particles (Printex 90) and crocidolite asbestos fibers were used as well-characterized reference materials and compared with three commercial samples of multiwalled carbon nanotubes (MWCNTs). Doses were identified in 2D and 3D cultures in order to minimize acute toxicity and to reflect realistic occupational exposures in humans and in previous inhalation studies in rodents. Under serum-free conditions, exposure of nonadherent primary murine bone marrow-derived macrophages to 0.5 μg/ml (0.38 μg/cm²) of crocidolite asbestos fibers or MWCNTs, but not carbon black, induced macrophage differentiation into epithelioid cells and formation of stable aggregates with the characteristic morphology of granulomas. Formation of multinucleated giant cells was also induced by asbestos fibers or MWCNTs in this 3D <it>in vitro </it>model. After 7-14 days, macrophages exposed to high aspect ratio nanomaterials co-expressed proinflammatory (M1) as well as profibrotic (M2) phenotypic markers.</p> <p>Conclusions</p> <p>Induction of epithelioid granulomas appears to correlate with high aspect ratio and complex 3D structure of carbon nanotubes, not with their iron content or surface area. This model offers a time- and cost-effective platform to evaluate the potential of engineered high aspect ratio nanomaterials, including carbon nanotubes, nanofibers, nanorods and metallic nanowires, to induce granulomas following inhalation.</p

A Phase transition in acoustic propagation in 2D random liquid media

Acoustic wave propagation in liquid media containing many parallel air-filled cylinders is considered. A self-consistent method is used to compute rigorously the propagation, incorporating all orders of multiple scattering. It is shown that under proper conditions, multiple scattering leads to a peculiar phase transition in acoustic propagation. When the phase transition occurs, a collective behavior of the cylinders appears and the acoustic waves are confined in a region of space in the neighborhood of the transmission source. A novel phase diagram is used to describe such phase transition. Originally submitted on April 6, 99.Comment: 5 pages, 5 color figure

Inhibition in multiclass classification

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

Inhibition in multiclass classification

The role of inhibition is investigated in a multiclass support vector machine formalism inspired by the brain structure of insects. The so-called mushroom bodies have a set of output neurons, or classification functions, that compete with each other to encode a particular input. Strongly active output neurons depress or inhibit the remaining outputs without knowing which is correct or incorrect. Accordingly, we propose to use a classification function that embodies unselective inhibition and train it in the large margin classifier framework. Inhibition leads to more robust classifiers in the sense that they perform better on larger areas of appropriate hyperparameters when assessed with leave-one-out strategies. We also show that the classifier with inhibition is a tight bound to probabilistic exponential models and is Bayes consistent for 3-class problems. These properties make this approach useful for data sets with a limited number of labeled examples. For larger data sets, there is no significant comparative advantage to other multiclass SVM approaches

Digging into acceptor splice site prediction : an iterative feature selection approach

Feature selection techniques are often used to reduce data dimensionality, increase classification performance, and gain insight into the processes that generated the data. In this paper, we describe an iterative procedure of feature selection and feature construction steps, improving the classification of acceptor splice sites, an important subtask of gene prediction. We show that acceptor prediction can benefit from feature selection, and describe how feature selection techniques can be used to gain new insights in the classification of acceptor sites. This is illustrated by the identification of a new, biologically motivated feature: the AG-scanning feature. The results described in this paper contribute both to the domain of gene prediction, and to research in feature selection techniques, describing a new wrapper based feature weighting method that aids in knowledge discovery when dealing with complex datasets

Broadside radar echoes from ionized trails

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/77210/1/AIAA-2347-553.pd