Investigation of passive flow control techniques to enhance the stall characteristics of a microlight aircraft

This report investigates the enhancement of aerodynamic stall characteristics of a Skyranger microlight aircraft by the use of passive flow control techniques, namely vortex generators and turbulators. Each flow control device is designed and scaled to application conditions. Force balance measurements and surface oil flow visualisation are carried out on a half-model of the microlight to further investigate the nature of the flow on the aircraft with and without the flow control devices. The results indicate a clear advantage to the use of turbulators compared with vortex generators. Turbulators increased the maximum lift coefficient by 2.8%, delayed the onset of stall by increasing the critical angle by 17.6% and reduced the drag penalty at both lower (pre-stall) and higher angles of attack by 8% compared to vortex generators. With vortex generators applied, the results indicated a delayed stall with an increase in the critical angle by 2% and a reduced drag penalty at higher angles of attack

Parallel Computing for Probabilistic Response Analysis of High Temperature Composites

The objective of this Phase I research was to establish the required software and hardware strategies to achieve large scale parallelism in solving PCM problems. To meet this objective, several investigations were conducted. First, we identified the multiple levels of parallelism in PCM and the computational strategies to exploit these parallelisms. Next, several software and hardware efficiency investigations were conducted. These involved the use of three different parallel programming paradigms and solution of two example problems on both a shared-memory multiprocessor and a distributed-memory network of workstations

A classification framework for drug relapse prediction

This paper proposes a framework for relapse prediction using Artificial Neural Networkalgorithms among drug addicts at Pusat Rawatan Inabah. The data collected will be miningthrough Artificial Neural Network algorithms to generate patterns and useful knowledge andthen automatically classifying the relapse possibility. This research collaborates with PusatRawatan Inabah, which is one of the rehabilitation centers that provide a specific treatment torehabilitate the drug addicts from addiction. We expect that among the classification datamining algorithms, Artificial Intelligence Neural Network (ANN) is one of the bestalgorithms to predict relapse among drug addicts. This may help the rehabilitation center topredict relapse individually and the prediction result is hoped to prevent drug addicts fromrelapse.Keywords: classification; artificial neural network; drug addiction; Inabah rehabilitation

Polymer translocation through a nanopore - a showcase of anomalous diffusion

The translocation dynamics of a polymer chain through a nanopore in the absence of an external driving force is analyzed by means of scaling arguments, fractional calculus, and computer simulations. The problem at hand is mapped on a one dimensional {\em anomalous} diffusion process in terms of reaction coordinate $s$ (i.e. the translocated number of segments at time $t$) and shown to be governed by an universal exponent $\alpha = 2/(2\nu+2-\gamma_1)$ whose value is nearly the same in two- and three-dimensions. The process is described by a {\em fractional} diffusion equation which is solved exactly in the interval $0 <s < N$ with appropriate boundary and initial conditions. The solution gives the probability distribution of translocation times as well as the variation with time of the statistical moments: $$, and $- < s(t)>^2$ which provide full description of the diffusion process. The comparison of the analytic results with data derived from extensive Monte Carlo (MC) simulations reveals very good agreement and proves that the diffusion dynamics of unbiased translocation through a nanopore is anomalous in its nature.Comment: 5 pages, 3 figures, accepted for publication in Phys. Rev.

Abundance of unknots in various models of polymer loops

A veritable zoo of different knots is seen in the ensemble of looped polymer chains, whether created computationally or observed in vitro. At short loop lengths, the spectrum of knots is dominated by the trivial knot (unknot). The fractional abundance of this topological state in the ensemble of all conformations of the loop of $N$ segments follows a decaying exponential form, $\sim \exp (-N/N_0)$, where $N_0$ marks the crossover from a mostly unknotted (ie topologically simple) to a mostly knotted (ie topologically complex) ensemble. In the present work we use computational simulation to look closer into the variation of $N_0$ for a variety of polymer models. Among models examined, $N_0$ is smallest (about 240) for the model with all segments of the same length, it is somewhat larger (305) for Gaussian distributed segments, and can be very large (up to many thousands) when the segment length distribution has a fat power law tail.Comment: 13 pages, 6 color figure

Residence Time Statistics for Normal and Fractional Diffusion in a Force Field

We investigate statistics of occupation times for an over-damped Brownian particle in an external force field. A backward Fokker-Planck equation introduced by Majumdar and Comtet describing the distribution of occupation times is solved. The solution gives a general relation between occupation time statistics and probability currents which are found from solutions of the corresponding problem of first passage time. This general relationship between occupation times and first passage times, is valid for normal Markovian diffusion and for non-Markovian sub-diffusion, the latter modeled using the fractional Fokker-Planck equation. For binding potential fields we find in the long time limit ergodic behavior for normal diffusion, while for the fractional framework weak ergodicity breaking is found, in agreement with previous results of Bel and Barkai on the continuous time random walk on a lattice. For non-binding potential rich physical behaviors are obtained, and classification of occupation time statistics is made possible according to whether or not the underlying random walk is recurrent and the averaged first return time to the origin is finite. Our work establishes a link between fractional calculus and ergodicity breaking.Comment: 12 page

The Energy Landscape, Folding Pathways and the Kinetics of a Knotted Protein

The folding pathway and rate coefficients of the folding of a knotted protein are calculated for a potential energy function with minimal energetic frustration. A kinetic transition network is constructed using the discrete path sampling approach, and the resulting potential energy surface is visualized by constructing disconnectivity graphs. Owing to topological constraints, the low-lying portion of the landscape consists of three distinct regions, corresponding to the native knotted state and to configurations where either the N- or C-terminus is not yet folded into the knot. The fastest folding pathways from denatured states exhibit early formation of the N-terminus portion of the knot and a rate-determining step where the C-terminus is incorporated. The low-lying minima with the N-terminus knotted and the C-terminus free therefore constitute an off-pathway intermediate for this model. The insertion of both the N- and C-termini into the knot occur late in the folding process, creating large energy barriers that are the rate limiting steps in the folding process. When compared to other protein folding proteins of a similar length, this system folds over six orders of magnitude more slowly.Comment: 19 page

Epitaxial Catalyst-Free Growth of InN Nanorods onc-Plane Sapphire

We report observation of catalyst-free hydride vapor phase epitaxy growth of InN nanorods. Characterization of the nanorods with transmission electron microscopy, and X-ray diffraction show that the nanorods are stoichiometric 2H–InN single crystals growing in the [0001] orientation. The InN rods are uniform, showing very little variation in both diameter and length. Surprisingly, the rods show clear epitaxial relations with thec-plane sapphire substrate, despite about 29% of lattice mismatch. Comparing catalyst-free with Ni-catalyzed growth, the only difference observed is in the density of nucleation sites, suggesting that Ni does not work like the typical vapor–liquid–solid catalyst, but rather functions as a nucleation promoter by catalyzing the decomposition of ammonia. No conclusive photoluminescence was observed from single nanorods, while integrating over a large area showed weak wide emissions centered at 0.78 and at 1.9 eV

Nerve Growth Factor Stimulates Interaction of Cayman Ataxia Protein BNIP-H/Caytaxin with Peptidyl-Prolyl Isomerase Pin1 in Differentiating Neurons

Mutations in ATCAY that encodes the brain-specific protein BNIP-H (or Caytaxin) lead to Cayman cerebellar ataxia. BNIP-H binds to glutaminase, a neurotransmitter-producing enzyme, and affects its activity and intracellular localization. Here we describe the identification and characterization of the binding between BNIP-H and Pin1, a peptidyl-prolyl cis/trans isomerase. BNIP-H interacted with Pin1 after nerve growth factor-stimulation and they co-localized in the neurites and cytosol of differentiating pheochromocytoma PC12 cells and the embryonic carcinoma P19 cells. Deletional mutagenesis revealed two cryptic binding sites within the C-terminus of BNIP-H such that single point mutants affecting the WW domain of Pin1 completely abolished their binding. Although these two sites do not contain any of the canonical Pin1-binding motifs they showed differential binding profiles to Pin1 WW domain mutants S16E, S16A and W34A, and the catalytically inert C113A of its isomerase domain. Furthermore, their direct interaction would occur only upon disrupting the ability of BNIP-H to form an intramolecular interaction by two similar regions. Furthermore, expression of Pin1 disrupted the BNIP-H/glutaminase complex formation in PC12 cells under nerve growth factor-stimulation. These results indicate that nerve growth factor may stimulate the interaction of BNIP-H with Pin1 by releasing its intramolecular inhibition. Such a mechanism could provide a post-translational regulation on the cellular activity of BNIP-H during neuronal differentiation. (213 words