Suchergebnisse

1 Development of the Tractor -- 2 Thermodynamic Principles of Internal-Combustion Engines -- 3 Internal-Combustion Engine Cycles -- 4 Fuels and Combustion -- 5 Engine Design -- 6 Electrical Systems -- 7 Engine Accessories -- 8 Lubrication -- 9 Human Factors in Tractor Design -- 10 Traction -- 11 Mechanics of the Tractor Chassis -- 12 Hydraulic Systems and Controls -- 13 Transmissions and Drive Trains -- 14 Tractor Tests and Performance -- Appendixes -- A Standards for Agricultural Tractors -- B Standard Graphical Symbols -- C Agricultural Tractor Tire Loadings, Torque Factors, and Inflation Pressures—SAE J709d -- D Conversion Factors.

Purpose. To investigate relationships among youth risk behaviors and demographic factors using an adolescent age group approach. Design. Cross-sectional data from a randomly selected population. Risk behaviors were compared within specific demographic factors and by adolescent age groups. Setting. Racially diverse, inner-city neighborhoods in two midwestern cities. Subjects. Teenagers (n = 1350) and parents (n = 1350) of the teenagers. Measures. Truancy; arrested/picked up by police; weapon carrying; fighting; sexual intercourse; tobacco, alcohol, and other drug use; demographic factors; and family structure. Results. Youth mean age was 15.4 (±1.7) years and 52% were female; racial/ethnic characteristics were 47% White, 22% Black, 19% Hispanic, and 10% Native American. Parents' mean age was 42.2 (±8.4) years and 81% were female. χ2 analyses indicated numerous significant (p < .05) youth risk behavior differences within the demographic factors and that many of the differences varied by adolescent age group. For example, risk behavior differences within racial/ethnic groups were most profound in the middle and older age groups, whereas risk behavior differences within parent income, education levels, and family structure were most apparent in the younger age groups. Of the demographic factors, family structure was most frequently associated with the risk behaviors. Conclusions. The results generally suggest that the relationships among risk behaviors and demographic factors vary within the adolescent age groups included in this study. The results will be useful for developing age-appropriate prevention programs for youth who fit the profile for these risk behaviors. The study protocol also includes specific sampling methods that may be useful for future studies that intend to collect data from difficult-to-reach populations.