Navigation Errors Introduced By Ground Vehicle Dynamics

An analysis of navigational accuracy when influenced by ground vehicle dynamics is presented. Tests beds outfitted with various sensor suites were used to collect data when normal and extreme driving maneuvers are executed. The data was run through an extended Kalman filter to produce a navigation solution. The Kalman filter inputs varied on each test bed, using both automotive and tactical grade Inertial Measurement Units (IMU). The position, velocity, and course measurements were obtained from a DGPS unit mounted on the vehicles and used as a truth measurement when exploring dead reckoning error. Additional measurements, such as wheel speed, radar speed, and magnetometer heading, were added to improve the robustness and reliability of the solution. The results of the work show the effect of both longitudinal and lateral vehicle slip on the navigation solution. In addition, the attempt of the various sensors to correct the errors is investigated. Reprinted with permission from The Institute of Navigation (http://ion.org/) and The Proceedings of the 18th International Technical Meeting of the Satellite Division of The Institute of Navigation, (pp. 302-316). Fairfax, VA: The Institute of Navigation

Performance Improvements for a Large-scale Geological Simulation

AbstractGeological models have been successfully used to identify and study geothermal energy resources. Many computer simulations based on these models are data-intensive applications. Large-scale geological simulations require high performance computing (HPC) techniques to run within reasonable time constraints and performance levels. One research area that can benefit greatly from HPC techniques is the modeling of heat flow beneath the Earth's surface. This paper describes the application of HPC techniques to increase the scale of research with a well-established geological model. Recently, a serial C++ application based on this geological model was ported to a parallel HPC applications using MPI. An area of focus was to increase the performance of the MPI version to enable state or regional scale simulations using large numbers of processors. First, synchronous communications among MPI processes was replaced by overlapping communication and computation (asynchronous communication). Asynchronous communication improved performance over synchronous communications by averages of 28% using 56 cores in one environment and 46% using 56 cores in another. Second, an approach for load balancing involving repartitioning the data at the start of the program resulted in runtime performance improvements of 32% using 48 cores in the first environment and 14% using 24 cores in the second when compared to the asynchronous version. An additional feature, modeling of erosion, was also added to the MPI code base. The performance improvement techniques under erosion were less effective

The Effects of High Volume Aquatic Plyometric Training on Vertical Jump, Muscle Power, and Torque

The purpose of this study was to examine the effects of high volume aquatic-based plyometrics versus lower volume land and aquatic plyometric training on vertical jump (VJ), muscular peak power and torque in the dominant knee. Thirty-nine adult participants were randomly assigned to 1 of 4 groups: aquatic group 1 (APT1), aquatic group 2 (APT2), land group (LPT1), and control group (CON). All groups performed a 6-week plyometric training program. The APT1 and LPT performed the same volume of training where, APT2 doubled the volume. All participants were pre- and post-tested on performance variables. A 4 (group) X 2 (time) ANOVA with repeated measures was used to determine differences between the performance variables. We found no significant differences between groups for all tested variables. However, APT2 showed the greatest increased average in the performance variables. The high volume aquatic plyometric protocol is useful to help increase performance and minimize muscle soreness

Corn, 2006

William J. Wiebold is a Professor of Plant Sciences and State Extension Specialist; Howard L. Mason is a Senior Research Specialist; Delbert Knerr, Ri chard W. Hasty, David M. Schwab, and Scotty L. Smothers are Research Specialists; Travis Belt is a Research Associate in Plant Sciences and Bruce Burdick is the Superintendent of the Hundl ey-Whaley Research Center.Compares hybrids and includes experimental procedures, seed corn characteristics and seed corn company addresses

The Comparative Pathology of Genetically Engineered Mouse Models for Neuroendocrine Carcinomas of the Lung

IntroductionBecause small-cell lung carcinomas (SCLC) are seldom resected, human materials for study are limited. Thus, genetically engineered mouse models (GEMMs) for SCLC and other high-grade lung neuroendocrine (NE) carcinomas are crucial for translational research.MethodsThe pathologies of five GEMMs were studied in detail and consensus diagnoses reached by four lung cancer pathology experts. Hematoxylin and Eosin and immunostained slides of over 100 mice were obtained from the originating and other laboratories and digitalized. The GEMMs included the original Rb/p53 double knockout (Berns Laboratory) and triple knockouts from the Sage, MacPherson, and Jacks laboratories (double knockout model plus loss of p130 [Sage laboratory] or loss of Pten [MacPherson and Jacks laboratories]). In addition, a GEMM with constitutive co-expression of SV40 large T antigen and Ascl1 under the Scgb1a1 promoter from the Linnoila laboratory were included.ResultsThe lung tumors in all of the models had common as well as distinct pathological features. All three conditional knockout models resulted in multiple pulmonary tumors arising mainly from the central compartment (large bronchi) with foci of in situ carcinoma and NE cell hyperplasia. They consisted of inter- and intra-tumor mixtures of SCLC and large-cell NE cell carcinoma in varying proportions. Occasional adeno- or large-cell carcinomas were also seen. Extensive vascular and lymphatic invasion and metastases to the mediastinum and liver were noted, mainly of SCLC histology. In the Rb/p53/Pten triple knockout model from the MacPherson and Jacks laboratories and in the constitutive SV40/T antigen model many peripherally arising non–small-cell lung carcinoma tumors having varying degrees of NE marker expression were present (non–small-cell lung carcinoma-NE tumors). The resultant histological phenotypes were influenced by the introduction of specific genetic alterations, by inactivation of one or both alleles of specific genes, by time from Cre activation and by targeting of lung cells or NE cell subpopulations.ConclusionThe five GEMM models studied are representative for the entire spectrum of human high-grade NE carcinomas and are also useful for the study of multistage pathogenesis and the metastatic properties of these tumors. They represent one of the most advanced forms of currently available GEMM models for the study of human cancer

The Comparative Pathology of Genetically Engineered Mouse Models for Neuroendocrine Carcinomas of the Lung

Introduction: Because small-cell lung carcinomas (SCLC) are seldom resected, human materials for study are limited. Thus, genetically engineered mouse models (GEMMs) for SCLC and other high-grade lung neuroendocrine (NE) carcinomas are crucial for translational research. Methods: The pathologies of five GEMMs were studied in detail and consensus diagnoses reached by four lung cancer pathology experts. Hematoxylin and Eosin and immunostained slides of over 100 mice were obtained from the originating and other laboratories and digitalized. The GEMMs included the original Rb/p53 double knockout (Berns Laboratory) and triple knockouts from the Sage, MacPherson, and Jacks laboratories (double knockout model plus loss of p130 [Sage laboratory] or loss of Pten [MacPherson and Jacks laboratories]). In addition, a GEMM with constitutive co-expression of SV40 large T antigen and Ascl1 under the Scgb1a1 promoter from the Linnoila laboratory were included. Results: The lung tumors in all of the models had common as well as distinct pathological features. All three conditional knockout models resulted in multiple pulmonary tumors arising mainly from the central compartment (large bronchi) with foci of in situ carcinoma and NE cell hyperplasia. They consisted of inter- and intra-tumor mixtures of SCLC and large-cell NE cell carcinoma in varying proportions. Occasional adeno- or large-cell carcinomas were also seen. Extensive vascular and lymphatic invasion and metastases to the mediastinum and liver were noted, mainly of SCLC histology. In the Rb/p53/Pten triple knockout model from the MacPherson and Jacks laboratories and in the constitutive SV40/T antigen model many peripherally arising non-small-cell lung carcinoma tumors having varying degrees of NE marker expression were present (non-small-cell lung carcinoma-NE tumors). The resultant histological phenotypes were influenced by the introduction of specific genetic alterations, by inactivation of one or both alleles of specific genes, by time from Cre activation and by targeting of lung cells or NE cell subpopulations. Conclusion: The five GEMM models studied are representative for the entire spectrum of human high-grade NE carcinomas and are also useful for the study of multistage pathogenesis and the metastatic properties of these tumors. They represent one of the most advanced forms of currently available GEMM models for the study of human cancer. Key Words: Neuroendocrine carcinomas; Small-cell lung carcinoma; Lung carcinoma; Non–small-cell lung cancer; Genetically engineered mouse models; Patholog

Corn, 2005

William J. Wiebold is a Professor of Plant Sciences and State Extension Specialist; Howard L. Mason is a Senior Research Specialist; Delbert Knerr, Richard W. Hasty, Eddie G. Adams, David M. Schwab, and Scotty L. Smothers are Research Specialists; Travis Belt is a Research Associate in Plant Sciences and Bruce Burdick is the Superintendent of the Hundley-Whaley Research Center.Compares hybrids and includes experimental procedures, seed corn characteristics and seed corn company addresses