Parasitism of \u3ci\u3eCidia\u3c/i\u3e Spp. (Lepidoptera: Tortricidae) on \u3ci\u3eSophora Chrysophylla\u3c/i\u3e (Fabaceae) Along an Elevation Gradient of Dry Subalpine Forest on Mauna Kea, Hawaii

The biology and ecological importance of Hawaiian endemic Cydia spp. (Lepidoptera: Tortricidae) are poorly known. Cydia larvae arc an important food to palila, an endangered Hawaiian bird that inhabits Sophora woodlands on Mauna Kea, Hawaii. We quantified Cydia larval abundance in seeds of Sophora chrysophylla Salisbury (Fabaceae) and larval mortality caused by parasitism. Four new host plant associations are reported: C. crassicornis [Walsingham], C. fulsifalcella [Walsingham], C. obliqlla [Walsingham], and C. storeella [Walsingham]. Four parasitoid wasp species were consistently reared from larval Cydia: Calliephialtes grapholithae [Cresson], Diadegma blackburni [Cameron], Pristomerus hawaiiensis Perkins (Hymenoptera: Ichneumonidae), and Euderus metallicus [Ashmead] (Hymenoptera: Eulophidae). The three Ichneumonidae appear to be accidental introductions, while E. metallicus is likely to be native to Hawaii. Parasitism rates by all four wasps combined decreased with elevation from 94% at 1800 m to 20% at 2700 m

Parasitism of \u3ci\u3eCidia\u3c/i\u3e Spp. (Lepidoptera: Tortricidae) on \u3ci\u3eSophora Chrysophylla\u3c/i\u3e (Fabaceae) Along an Elevation Gradient of Dry Subalpine Forest on Mauna Kea, Hawaii

The biology and ecological importance of Hawaiian endemic Cydia spp. (Lepidoptera: Tortricidae) are poorly known. Cydia larvae arc an important food to palila, an endangered Hawaiian bird that inhabits Sophora woodlands on Mauna Kea, Hawaii. We quantified Cydia larval abundance in seeds of Sophora chrysophylla Salisbury (Fabaceae) and larval mortality caused by parasitism. Four new host plant associations are reported: C. crassicornis [Walsingham], C. fulsifalcella [Walsingham], C. obliqlla [Walsingham], and C. storeella [Walsingham]. Four parasitoid wasp species were consistently reared from larval Cydia: Calliephialtes grapholithae [Cresson], Diadegma blackburni [Cameron], Pristomerus hawaiiensis Perkins (Hymenoptera: Ichneumonidae), and Euderus metallicus [Ashmead] (Hymenoptera: Eulophidae). The three Ichneumonidae appear to be accidental introductions, while E. metallicus is likely to be native to Hawaii. Parasitism rates by all four wasps combined decreased with elevation from 94% at 1800 m to 20% at 2700 m

Robust increase in supply by vessel dilation in globally coupled microvasculature

Neuronal activity induces changes in blood flow by locally dilating vessels in the brain microvasculature. How can the local dilation of a single vessel increase flow-based metabolite supply, given that flows are globally coupled within microvasculature? Solving the supply dynamics for rat brain microvasculature, we find one parameter regime to dominate physiologically. This regime allows for robust increase in supply independent of the position in the network, which we explain analytically. We show that local coupling of vessels promotes spatially correlated increased supply by dilation

Model Order Reduction of Aeroservoelastic Model of Flexible Aircraft

This paper presents a holistic model order reduction (MOR) methodology and framework that integrates key technological elements of sequential model reduction, consistent model representation, and model interpolation for constructing high-quality linear parameter-varying (LPV) aeroservoelastic (ASE) reduced order models (ROMs) of flexible aircraft. The sequential MOR encapsulates a suite of reduction techniques, such as truncation and residualization, modal reduction, and balanced realization and truncation to achieve optimal ROMs at grid points across the flight envelope. The consistence in state representation among local ROMs is obtained by the novel method of common subspace reprojection. Model interpolation is then exploited to stitch ROMs at grid points to build a global LPV ASE ROM feasible to arbitrary flight condition. The MOR method is applied to the X-56A MUTT vehicle with flexible wing being tested at NASA/AFRC for flutter suppression and gust load alleviation. Our studies demonstrated that relative to the fullorder model, our X-56A ROM can accurately and reliably capture vehicles dynamics at various flight conditions in the target frequency regime while the number of states in ROM can be reduced by 10X (from 180 to 19), and hence, holds great promise for robust ASE controller synthesis and novel vehicle design

Genetic Algorithm-Based Model Order Reduction of Aeroservoelastic Systems with Consistant States

This paper presents a model order reduction framework to construct linear parameter-varying reduced-order models of flexible aircraft for aeroservoelasticity analysis and control synthesis in broad two-dimensional flight parameter space. Genetic algorithms are used to automatically determine physical states for reduction and to generate reduced-order models at grid points within parameter space while minimizing the trial-and-error process. In addition, balanced truncation for unstable systems is used in conjunction with the congruence transformation technique to achieve locally optimal realization and weak fulfillment of state consistency across the entire parameter space. Therefore, aeroservoelasticity reduced-order models at any flight condition can be obtained simply through model interpolation. The methodology is applied to the pitch-plant model of the X-56A Multi-Use Technology Testbed currently being tested at NASA Armstrong Flight Research Center for flutter suppression and gust load alleviation. The present studies indicate that the reduced-order model with more than 12 reduction in the number of states relative to the original model is able to accurately predict system response among all input-output channels. The genetic-algorithm-guided approach exceeds manual and empirical state selection in terms of efficiency and accuracy. The interpolated aeroservoelasticity reduced order models exhibit smooth pole transition and continuously varying gains along a set of prescribed flight conditions, which verifies consistent state representation obtained by congruence transformation. The present model order reduction framework can be used by control engineers for robust aeroservoelasticity controller synthesis and novel vehicle design

On-Line Loss of Control Detection Using Wavelets

Wavelet transforms are used for on-line detection of aircraft loss of control. Wavelet transforms are compared with Fourier transform methods and shown to more rapidly detect changes in the vehicle dynamics. This faster response is due to a time window that decreases in length as the frequency increases. New wavelets are defined that further decrease the detection time by skewing the shape of the envelope. The wavelets are used for power spectrum and transfer function estimation. Smoothing is used to tradeoff the variance of the estimate with detection time. Wavelets are also used as front-end to the eigensystem reconstruction algorithm. Stability metrics are estimated from the frequency response and models, and it is these metrics that are used for loss of control detection. A Matlab toolbox was developed for post-processing simulation and flight data using the wavelet analysis methods. A subset of these methods was implemented in real time and named the Loss of Control Analysis Tool Set or LOCATS. A manual control experiment was conducted using a hardware-in-the-loop simulator for a large transport aircraft, in which the real time performance of LOCATS was demonstrated. The next step is to use these wavelet analysis tools for flight test support