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The purpose of this study was to develop a regression equation to predict VO2max based on non-exercise (N-EX) data. All participants (N = 100), aged 18-65 years old, successfully completed a maximal graded exercise test (GXT) to assess VO2max (mean ± SD; 39.96 mL∙kg-¹∙min&sup-1; ± 9.54 mL∙kg-¹∙min-¹). The N-EX data collected just before the maximal GXT included the participant's age, gender, body mass index (BMI), perceived functional ability (PFA) to walk, jog, or run given distances, and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R = .93, SEE = 3.45 mL∙kg-¹∙min-¹, %SEE = 8.62): VO2max (mL∙kg-¹∙min-¹) = 48.0730 + (6.1779 x gender) - (0.2463 x age) - (0.6186 x BMI) + (0.7115 x PFA) + (0.6709 x PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (Rp = .91 and SEEp = 3.63 mL∙kg-¹∙min-¹); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (aged 18-65) with a similar cardiorespiratory fitness level. Based on standardized β-weights the PFA variable (0.41) was the most effective at predicting VO2max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO2max in adult men and women.

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How well students perform in mathematics and sciences continues to be a measure of a country's worth (Conference Board of the Mathematical Sciences [CBMS], 2012). Nations that want an educated citizenry have consistently studied ways in which to improve performance in mathematics (Claessens and Engel, 2013; Dearing et al., 2012; Draper and Siebert, 2004). More and more researchers have examined the relationship reading has on mathematics performance (Grimm, 2008; Halaar, Kovas, Dale, Petrill, and Plomin, 2012). This study was an effort to contribute to this growing body of knowledge. Therefore the purpose of this study was to examine what relationship exists between reading and mathematics and whether early reading performance could predict subsequent mathematics performance as measured by the Virginia Standards of Learning Assessments. Using a sample of students from a Virginia high school, this quantitative study utilized Virginia Standards of Learning (SOL) tests as instruments and Chi-square Test of Association as the analysis to address the research questions: 1. What is the relationship between Virginia Standards of Learning (SOL) reading performance and SOL mathematics performance at each grade level in Grade 3 through Grade 8? 2. What is the relationship between SOL reading performance in Grade 3 and subsequent performance on Virginia SOL End-of-Course Algebra I assessment? 3. To what extent does SOL reading performance in Grade 3 predict subsequent performance on Virginia SOL End-of-Course Algebra I assessment? Virginia SOL reading performance was found to be associated with mathematics performance at each grade level. Reading performance at Grade 3 was not found to be associated with Algebra I EOC performance. Grade 5, Grade 6, Grade 7, and Grade 8 reading performance were all found to be associated with Algebra I EOC performance. As a limitation, this study utilized data from assessments designed to assess the 2001 Virginia SOL standards, which have since been updated. Therefore should be replicated using the current standards. The results of this study could be used to assist teacher leaders, principals, division leaders, and teacher preparation program leaders with working with teachers to address reading and mathematics deficiencies in a different way. / Ed. D.

The purpose of this study was to determine the value of the Non Cognitive Questionnaire (NCQ) and the Scholastic Aptitude Test (SAT) in predicting the academic achievement of first year female engineering students. Ancis and Sedlacek (1997) studied non-cognitive variables with a general population of undergraduate women. Their study validated the NCQ as a predictor of academic success for women students. The present study extends the work of Ancis and Sedlacek to examine female engineering students, a group for which no similar study has yet been published.Participants included 100 female first-year engineering students at a large, public Doctoral Research â Extensive institution located in the mid-Atlantic region of the United States. By race or ethnicity, the participants were White, Non-Hispanic (81%), Black Non-Hispanic (9%), Asian or Pacific Islander (4%), Hispanic or Latino (1%), Non-Resident Alien (1%), and Unknown Race or Ethnicity (6%). This study defined academic achievement as first semester Grade Point Average, which was used as the dependent variable. Participants completed the NCQ during summer orientation. NCQ scale scores and SAT Verbal and Math scores were used as independent variables in a step-wise regression analysis.The major finding of this study was that the NCQ scale scores did not add to the predictive value of the SAT scores in determining the first semester GPA of female engineering students. This was an unexpected finding in light of previous research that had documented the value of using non-cognitive variables, and specifically the NCQ, to predict the academic success of groups that are a minority in their educational settings.Because the major finding of this study is at odds with a large body of similar studies, the most important implications of this study relate to understanding this difference. Included in the discussion are questions about the methodology used in previous NCQ studies and about the influence of the single institution that has been the site of almost all previous NCQ research. / Master of Arts

ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / The surprise failure of two NASA Space Shuttles and the premature failures of satellite subsystem equipment on NASA satellites are motivating NASA to adopt an engineering discipline that uses telemetry specifically developed for preventing surprise equipment failures. The NASA Orion spacecraft is an Apollo module-like capsule planned to replace the NASA Space Shuttle reusable launch vehicle for getting astronauts to space and return to the earth safely as well as a crew escape vehicle stored at the ISS. To do so, NASA is adopting a non-Markov reliability paradigm for measuring equipment life based on the prognostic and health management program on the Air Force F-35 Joint Strike Fighter. The decision is based on the results from the prognostic analysis completed on the Space Shuttle Challenger and Columbia that identified the information that was present but was ignored for a variety of reasons. The goal of a PHM is to produce equipment that will not fail prematurely. It includes using predictive algorithms to measure equipment usable life. Equipment with transient behavior caused from accelerated of parts will fail prematurely with 100% certainty. For many decades, it was believed that test equipment and software used to in testing and noise from communications equipment were the cause of most transient behavior. With the processing speed of today's processors, transient behavior is caused from at least one part suffering from accelerated aging. Transient behavior is illustrated in equipment telemetry in a prognostic analysis. Telemetry is equipment performance information and equipment performance has been used to increase reliability, but performance is unrelated to equipment remaining usable life and so equipment should be failing prematurely. A PHM requires equipment telemetry for analysis and so analog telemetry will be available from all Orion avionics equipment. Replacing equipment with a measured remaining usable life of less than one year will stop the premature and surprise equipment failures from occurring during future manned and unmanned space missions.

ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / Launch vehicle equipment reliability is driven by infant mortality failures, which can be eliminated using a prognostic analysis prior, during and/or after the exhaustive and comprehensive dynamic environmental factory acceptance testing. Measuring and confirming equipment performance is completed to increase equipment reliability by identifying equipment that fails during test for repair/replacement. To move to the 100% reliability domain, equipment dynamic environmental factory testing should be followed by a prognostic analysis to measure equipment usable life and identify the equipment that will fail prematurely. During equipment testing, only equipment performance is measured and equipment performance is unrelated to equipment reliability making testing alone inadequate to produce equipment with 100% reliability. A prognostic analysis converts performance measurements into an invasive usable life measurement by sharing test data used to measure equipment performance. Performance data is converted to usable life data provides a time-to-failure (TTF) in minutes/hours/days/months for equipment that will fail within the first year of use, allowing the production of equipment with 100% reliability.

ITC/USA 2011 Conference Proceedings / The Forty-Seventh Annual International Telemetering Conference and Technical Exhibition / October 24-27, 2011 / Bally's Las Vegas, Las Vegas, Nevada / Satellite and launch vehicles continues to suffer from catastrophic infant mortality failures. NASA now requires satellite suppliers to provide on-orbit satellite delivery and a free satellite and launch vehicle in the event of a catastrophic infant mortality failure. A high infant mortality failure rate demonstrates that the factory acceptance test program alone is inadequate for producing 100% reliability space vehicle equipment. This inadequacy is caused from personnel only measuring equipment performance during ATP and performance is unrelated to reliability. Prognostic technology uses pro-active diagnostics, active reasoning and proprietary algorithms that illustrate deterministic data for prognosticians to identify piece-parts, components and assemblies that will fail within the first year of use allowing this equipment to be repaired or replaced while still on the ground. Prognostic technology prevents equipment failures and so is pro-active. Adding prognostic technology will identify all unreliable equipment prior to shipment to the launch pad producing 100% reliable equipment and will eliminate launch failures, launch pad delays, on-orbit infant mortalities, surprise in-orbit failures. Moving to the 100% reliable equipment extends on-orbit equipment usable life.