Centaur Test Bed (CTB) for Cryogenic Fluid Management

Future missions such as NASA s space exploration vision and DOD satellite servicing will require significant increases in the understanding and knowledge of space based cryogenic fluid management (CFM), including the transfer and storage of cryogenic fluids. Existing CFM capabilities are based on flight of upper stage cryogenic vehicles, scientific dewars, a few dedicated flight demonstrations and ground testing. This current capability is inadequate to support development of the CEV cryogenic propulsion system, other aspects of robust space exploration or the refueling of satellite cryo propulsion systems with reasonable risk. In addition, these technologies can provide significant performance increases for missions beyond low-earth orbit to enable manned missions to the Moon and beyond. The Centaur upper-stage vehicle can provide a low cost test platform for performing numerous flight demonstrations of the full breadth of required CFM technologies to support CEV development. These flight demonstrations can be performed as secondary mission objectives using excess LH2 and/or LO2 from the main vehicle propellant tanks following primary spacecraft separation at minimal cost and risk

Gaussian Nonlinear Line Attractor for Learning Multidimensional Data

The human brain’s ability to extract information from multidimensional data modeled by the Nonlinear Line Attractor (NLA), where nodes are connected by polynomial weight sets. Neuron connections in this architecture assumes complete connectivity with all other neurons, thus creating a huge web of connections. We envision that each neuron should be connected to a group of surrounding neurons with weighted connection strengths that reduces with proximity to the neuron. To develop the weighted NLA architecture, we use a Gaussian weighting strategy to model the proximity, which will also reduce the computation times significantly. Once all data has been trained in the NLA network, the weight set can be reduced using a locality preserving nonlinear dimensionality reduction technique. By reducing the weight sets using this technique, we can reduce the amount of outputs for recognition tasks. An appropriate distance measure can then be used for comparing testing data and the trained data when processed through the NLA architecture. It is observed that the proposed GNLA algorithm reduces training time significantly and is able to provide even better recognition using fewer dimensions than the original NLA algorithm. We have tested this algorithm and showed that it works well in different datasets, including the EO Synthetic Vehicle database and the Sheffield face database

Gaussian Weighted Neighborhood Connectivity of Nonlinear Line Attractor for Learning Complex Manifolds

The human brain has the capability to process high quantities of data quickly for detection and recognition tasks. These tasks are made simpler by the understanding of data, which intentionally removes redundancies found in higher dimensional data and maps the data onto a lower dimensional space. The brain then encodes manifolds created in these spaces, which reveal a specific state of the system. We propose to use a recurrent neural network, the nonlinear line attractor (NLA) network, for the encoding of these manifolds as specific states, which will draw untrained data towards one of the specific states that the NLA network has encoded. We propose a Gaussian-weighted modular architecture for reducing the computational complexity of the conventional NLA network. The proposed architecture uses a neighborhood approach for establishing the interconnectivity of neurons to obtain the manifolds. The modified NLA network has been implemented and tested on the Electro-Optic Synthetic Vehicle Model Database created by the Air Force Research Laboratory (AFRL), which contains a vast array of high resolution imagery with several different lighting conditions and camera views. It is observed that the NLA network has the capability for representing high dimensional data for the recognition of the objects of interest through its new learning strategy. A nonlinear dimensionality reduction scheme based on singular value decomposition has found to be very effective in providing a low dimensional representation of the dataset. Application of the reduced dimensional space on the modified NLA algorithm would provide fast and more accurate recognition performance for real time applications

Identification and Morphological Variation of an Invasive Parasite in Introduced and Native Lizards

Exotic species can threaten biodiversity by introducing parasites to native hosts. Thus, it is critical to identify if the same parasite species is infecting both native and exotic hosts. Developmental or environmentally induced variation in morphology, however, may complicate identification. Geckos are one of the most successful invasive families of vertebrates and are known to host lung parasites, pentastomids of the genus Raillietiella. Raillietiellids have a cosmopolitan distribution, which in part, may have been facilitated by the introductions of their hosts. Indeed, Raillietiella frenatus, a Southeast Asian parasite, has been reported in Texas (TX) from the exotic Mediterranean gecko, Hemidactylus turcicus. Here we report on the recent introduction (between 1998 and 2008) of a Raillietiella sp. into an established population of H. turcicus in Louisiana (LA). More critically, we found infections in native green anoles, a new host record for pentastomes. Upon sequencing 604 bp of the pentastome’s cytochrome c oxidase gene, we observed identical sequences from parasites of anoles and geckos. In fact, there was no sequence variation between published sequences of R. frenatus from geckos and cane toads in Australia. Interestingly, we found that traditional taxonomic analyses based on hook dimensions would have led to the false conclusion of two pentastome species within H. turcicus. But, as in Kelehear et al. (2011), when pentastome body size is accounted for the distinction between the two groups disappears. These results along with prior moulting studies on R. frenatus suggest hook size varies ontogenetically. Nonetheless, even after accounting for pentastome body size, hook dimensions differ significantly between host species. This result suggests these traits may be plastic as a result of host environment, but quantitative genetic experiments will be needed to disentangle phenotypic plasticity from genetic variation

Identification and Morphological Variation of an Invasive Parasite in Introduced and Native Lizards

Exotic species can threaten biodiversity by introducing parasites to native hosts. Thus, it is critical to identify if the same parasite species is infecting both native and exotic hosts. Developmental or environmentally induced variation in morphology, however, may complicate identification. Geckos are one of the most successful invasive families of vertebrates and are known to host lung parasites, pentastomids of the genus Raillietiella. Raillietiellids have a cosmopolitan distribution, which in part, may have been facilitated by the introductions of their hosts. Indeed, Raillietiella frenatus, a Southeast Asian parasite, has been reported in Texas (TX) from the exotic Mediterranean gecko, Hemidactylus turcicus. Here we report on the recent introduction (between 1998 and 2008) of a Raillietiella sp. into an established population of H. turcicus in Louisiana (LA). More critically, we found infections in native green anoles, a new host record for pentastomes. Upon sequencing 604 bp of the pentastome’s cytochrome c oxidase gene, we observed identical sequences from parasites of anoles and geckos. In fact, there was no sequence variation between published sequences of R. frenatus from geckos and cane toads in Australia. Interestingly, we found that traditional taxonomic analyses based on hook dimensions would have led to the false conclusion of two pentastome species within H. turcicus. But, as in Kelehear et al. (2011), when pentastome body size is accounted for the distinction between the two groups disappears. These results along with prior moulting studies on R. frenatus suggest hook size varies ontogenetically. Nonetheless, even after accounting for pentastome body size, hook dimensions differ significantly between host species. This result suggests these traits may be plastic as a result of host environment, but quantitative genetic experiments will be needed to disentangle phenotypic plasticity from genetic variation

Novel Pattern Recognition Techniques for Improved Target Detection in Hyperspectral Imagery

A fundamental challenge in target detection in hyperspectral imagery is spectral variability. In target detection applications, we are provided with a pure target signature; we do not have a collection of samples that characterize the spectral variability of the target. Another problem is that the performance of stochastic detection algorithms such as the spectral matched filter can be detrimentally affected by the assumptions of multivariate normality of the data, which are often violated in practical situations. We address the challenge of lack of training samples by creating two models to characterize the target class spectral variability --the first model makes no assumptions regarding inter-band correlation, while the second model uses a first-order Markovbased scheme to exploit correlation between bands. Using these models, we present two techniques for meeting these challenges-the kernel-based support vector data description (SVDD) and spectral fringe-adjusted joint transform correlation (SFJTC). We have developed an algorithm that uses the kernel-based SVDD for use in full-pixel target detection scenarios. We have addressed optimization of the SVDD kernel-width parameter using the golden-section search algorithm for unconstrained optimization. We investigated a proper number of signatures N to generate for the SVDD target class and found that only a small number of training samples is required relative to the dimensionality (number of bands). We have extended decision-level fusion techniques using the majority vote rule for the purpose of alleviating the problem of selecting a proper value of s 2 for either of our target variability models. We have shown that heavy spectral variability may cause SFJTC-based detection to suffer and have addressed this by developing an algorithm that selects an optimal combination of the discrete wavelet transform (DWT) coefficients of the signatures for use as features for detection. For most scenarios, our results show that our SVDD-based detection scheme provides low false positive rates while maintaining higher true positive rates than popular stochastic detection algorithms. Our results also show that our SFJTC-based detection scheme using the DWT coefficients can yield significant detection improvement compared to use of SFJTC using the original signatures and traditional stochastic and deterministic algorithms

Balanced and unbalanced welds for angle compression members.

It is common practice in Canada to balance fillet welds on angle members about the projection of the centroidal axis on the welded leg. In some instances, however, due to certain design restrictions, there is no room to place a balanced weld and the designer is forced to use an unbalanced weld. The Canadian Standards Association, as well as the American Specification and the British Standard, has approved this type of unbalanced connections. This approval was based on research carried out on tension members by Gibson and Wake in 1942. As a result of this research it has been assumed that the same conclusion applies to compression members. In order to determine the effects of the weld patterns on the behaviour of angle compression members, a series of ultimate compression tests and finite element analysis were performed. The experimental procedure consisted of applying a compressive load on two 50.8 x 50.8 x 6.35 mm (i.e. 2 x 2 x 1/4 in.) angle members connected at the ends to HSS\u27s with balanced and unbalanced weld patterns. Two different column heights were used which resulted in slenderness ratios that fall in the slender and intermediate range. The load was applied gradually until failure occurred in the specimen. The effect of unbalanced welds seems to be beneficial for slender angles but has a detrimental effect on the load carrying capacity of intermediate range angles. As the weld pattern changes from balanced to an unbalanced weld, the flexibility of the angle increases. The experimental failure loads are compared with the results from a finite element model. The welded angles were also designed as beam-columns according to CAN/CSA S16.1-M89 and the results were compared with the experimental failure loads. (Abstract shortened by UMI.)Dept. of Civil and Environmental Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1993 .S355. Source: Masters Abstracts International, Volume: 32-02, page: 0674. Adviser: M. C. Temple. Thesis (M.A.Sc.)--University of Windsor (Canada), 1993

Single-angle compression members welded by one leg to gusset plates.

Single-angle compression members are simple structural elements that are very difficult to analyse and design. These members are usually attached to other members by one leg only. Thus the load is applied eccentrically. To further complicate the problem, the principal axes of the angle do not coincide with the axes of the same or truss of which the angle is a part. Although it is known that the end conditions affect the ultimate load carrying capacity of these members, procedures have not been developed to do this as it is difficult to evaluate the end restraint in many practical cases. Different design practices were presented and evaluated using experimental test results obtained from previous research. The two generally accepted design procedures, the simple-column and the beam-column approaches, in general, underestimate the load carrying capacity of single-angle compression members attached by one leg to a gusset plate. There is a great variation between different design practices in the prediction of the compressive resistance of single-angle members. With that great variation it is difficult to determine the most appropriate design procedure to follow. The major objective of this research is to obtain a better understanding of the behaviour and load carrying capacity of single-angle compression members attached by one leg to a gusset plate. An experimental investigation was carried out and verified through the use of the finite element analysis. The effect of the gusset plate width, thickness and the unconnected length were studied. The effect of the weld length and pattern used in connecting the angle to the gusset plate was studied as well. It was found that the thickness and width of the gusset plate significantly affect the load carrying capacity, but the unconnected length has only a minor effect. The effect of the length of weld and the weld pattern used in the connection on the ultimate load carrying capacity can be neglected. It was found that the finite element method can be used, with a reasonable degree of accuracy, to predict the behaviour and load carrying capacity of these members. The finite element method was used to study some 1800 different combination of parameters. It was found that out-of-straightness, residual stresses, Young\u27s modulus of elasticity, and the unconnected gusset plate length do not have a great effect on the load carrying capacity. The most significant parameter is gusset plate thickness with the gusset plate width being the second most important parameter. An empirical design equation is proposed and illustrated by two design examples.Dept. of Civil and Environmental Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis1997 .S24. Source: Dissertation Abstracts International, Volume: 59-08, Section: B, page: 4308. Adviser: M. C. Temple. Thesis (Ph.D.)--University of Windsor (Canada), 1997

Genistein Affects HER2 Protein Concentration, Activation and Promoter Regulation via Estrogen Receptor-and non-Estrogen Receptor-Mediated Mechanisms

The HER2 proto-oncogene, a member of the epidermal growth factor receptor family, is overexpressed in 20–30% of breast cancers. Genistein, the main soy isoflavone, interacts with estrogen receptors (ER) and it is also a potent tyrosine kinase inhibitor. Previously, our laboratory found that genistein delayed mammary tumor onset in transgenic mice that overexpress HER2 gene. Our goal was to define the mechanism through which genistein affects mammary tumorigenesis inHER2 overexpressing mice. We hypothesized that genistein inhibits HER2 activation and expression through ER-dependent and ER-independent mechanisms. Genistein inhibited total HER2 protein expression and tyrosine phosphorylation in BT-474, an ERα (−) and ERβ (+) human breast cancer cell line, however, E2 had no effect. Taken together, these data suggest that genistein has an ER-independent inhibitory effect, presumably, through tyrosine kinase inhibition activity. Genistein at 1.0 μM mimicked E2 and down-regulated HER2 protein phosphorylation when BT-474 was co-transfected with ERα, but not ERβ. Although E2 and overexpression of HER2 can promote mammary tumorigenesis, an inverse relationship between ER expression and HER2 overexpression has been found in human breast cancer. We cloned a 500-bp promoter region upstream of theHER2 transcription initiation site. Co-transfection with ERα, but not with ERβ, down-regulated HER2promoter reporter in BT-474. At concentrations ≥1 μM, genistein inhibited HER2 promoter reporter in the absence of ERα. In conclusion, genistein at ≥1 μM inhibited HER2 protein expression, phosphorylation, and promoter activity through an ER-independent mechanism. In the presence of ERα, genistein mimicked E2 and inhibited HER2 protein phosphorylation. These data support genistein’s chemo-prevention and potential chemo-therapeutic roles in breast cancer