Hotfire testing of a SSME HPOTP with an annular hydrostatic bearing

A new fluid film bearing package has been tested in the Space Shuttle Main Engine (SSME) High Pressure Oxygen Turbopump (HPOTP). This fluid film element functions as both the pump end bearing and the preburner pump rear wear ring seal. Most importantly, it replaces a duplex ball bearing package which has been the primary life limiting component in the turbopump. The design and predicted performance of the turbopump are reviewed. Results are presented for measured pump and bearing performance during testing on the NASA Technology Test Bed (TTB) Engine located at MSFC. The most significant results were obtained from proximity probes located in the bearing bore which revealed large subsynchronous precession at ten percent of shaft speed during engine start which subsided prior to mainstage power levels and reappeared during engine shutdown at equivalent power levels below 65% of nominal. This phenomenon has been attributed to rotating stall in the diffuser. The proximity probes also revealed the location of the bearing in the bore for different operating speeds. Pump vibration characteristics were improved as compared to pumps tested with ball bearings. After seven starts and more than 700 seconds of testing, the pump showed no signs of performance degradation

Visualization methods for statistical analysis of microarray clusters

BACKGROUND: The most common method of identifying groups of functionally related genes in microarray data is to apply a clustering algorithm. However, it is impossible to determine which clustering algorithm is most appropriate to apply, and it is difficult to verify the results of any algorithm due to the lack of a gold-standard. Appropriate data visualization tools can aid this analysis process, but existing visualization methods do not specifically address this issue. RESULTS: We present several visualization techniques that incorporate meaningful statistics that are noise-robust for the purpose of analyzing the results of clustering algorithms on microarray data. This includes a rank-based visualization method that is more robust to noise, a difference display method to aid assessments of cluster quality and detection of outliers, and a projection of high dimensional data into a three dimensional space in order to examine relationships between clusters. Our methods are interactive and are dynamically linked together for comprehensive analysis. Further, our approach applies to both protein and gene expression microarrays, and our architecture is scalable for use on both desktop/laptop screens and large-scale display devices. This methodology is implemented in GeneVAnD (Genomic Visual ANalysis of Datasets) and is available at . CONCLUSION: Incorporating relevant statistical information into data visualizations is key for analysis of large biological datasets, particularly because of high levels of noise and the lack of a gold-standard for comparisons. We developed several new visualization techniques and demonstrated their effectiveness for evaluating cluster quality and relationships between clusters

The effect of a 12 week core training regimen on electromyographic activation in national-level junior swimmers

Knowledge of muscle activation during core training exercises over the duration of a training program would enhance our understanding of the physiological responses to training. The purpose of this study was to quantify the effect of a 12-week core training regimen on neuromuscular activation in swimmers. Ten national-level junior swimmers performed a core exercise regimen three times a week over a 12-week training period. Surface electromyographic (EMG) measurements from 6 core muscles were taken pre- (0 weeks), mid- (6 weeks) and post training (12 weeks). Analysis was carried out on the EMG activity during maximal voluntary isometric contractions (MVCs) and on the normalized and non-normalized EMG values during the core exercises. MVC EMG activity increased with the intervention in all muscles. The magnitudes of changes in MVC EMG activity were greater during the initial phase (effect sizes - standardized mean differences 0.32 to 1.01) compared to the second phase (effect sizes -0.20 to 1.04). Substantial reductions were observed in the normalized EMG data, with these effects being greater during the initial phase (effect sizes -1.54 to -0.28) compared to the second phase (effects sizes -1.12 to -0.22). There were also substantial reductions in non-normalized absolute EMG activity in both the initial (effect sizes -2.73 to -0.27) and second (effects sizes -1.27 to -0.20) phases. Over the 12 week training program substantial neuromuscular adaptations occurred in the core muscles; activation during the core exercises reduced, whilst activation during the MVCs increased. These adaptations are indicative of improvements in neuromuscular strength and efficiency. Changes in EMG data provide objective measures of neuromuscular adaptation which can inform future iterations of training regimens for athletic populations

GOLEM: an interactive graph-based gene-ontology navigation and analysis tool

BACKGROUND: The Gene Ontology has become an extremely useful tool for the analysis of genomic data and structuring of biological knowledge. Several excellent software tools for navigating the gene ontology have been developed. However, no existing system provides an interactively expandable graph-based view of the gene ontology hierarchy. Furthermore, most existing tools are web-based or require an Internet connection, will not load local annotations files, and provide either analysis or visualization functionality, but not both. RESULTS: To address the above limitations, we have developed GOLEM (Gene Ontology Local Exploration Map), a visualization and analysis tool for focused exploration of the gene ontology graph. GOLEM allows the user to dynamically expand and focus the local graph structure of the gene ontology hierarchy in the neighborhood of any chosen term. It also supports rapid analysis of an input list of genes to find enriched gene ontology terms. The GOLEM application permits the user either to utilize local gene ontology and annotations files in the absence of an Internet connection, or to access the most recent ontology and annotation information from the gene ontology webpage. GOLEM supports global and organism-specific searches by gene ontology term name, gene ontology id and gene name. CONCLUSION: GOLEM is a useful software tool for biologists interested in visualizing the local directed acyclic graph structure of the gene ontology hierarchy and searching for gene ontology terms enriched in genes of interest. It is freely available both as an application and as an applet at