Predictors of Satisfaction with Sport Leadership in Small-College Football Players

This study investigated eight possible predictors of satisfaction levels in smallcollege football players. The sample (N = 442) included eight nonscholarship football programs from the NCAA Division III or NAIA classifications. Measures included Zhang\u27s Revised Version of Chelladurai\u27s Leadership Scale for Sport, and a seven-item subscale of the Scale of Athlete Satisfaction. The six subscales of the Revised Leadership Scale for Sport each yielded a significant linear relationship with the satisfaction outcome measure: social support (I= .696), situational consideration (I= .665), positive feedback (r = .654), teaching and instruction (I= .627), democratic behaviors (I = .501), and autocratic behaviors (I= -.372). Minimal correlations were found between satisfaction and the two other predictors evaluated: each team\u27s win/loss percentage (I= .164) and each player\u27s estimated amount of playing time (r = .121). With the large sample size, these two modest correlations were also statistically significant. However, as neither accounted for more than 2% of the total variance in satisfaction levels, they are not likely to have practical significance. The predictors were also evaluated via stepwise multiple regression analysis to assess which combination(s) would account for more of the overall variance. Unfortunately, a mild case of multicollinearity made it difficult to attribute relative importance to the predictors. For example, the situational consideration subscale recorded especially high correlations with several of the other Revised Leadership Scale for Sport subscales. Overall, results indicate that specific coaching behaviors are more associated with player satisfaction in small-college players than are reported in previous samples of other types of athletes. As such, coaches are encouraged to provide support for players in off-the-field endeavors, offer positive feedback on performance goals, and combine knowledge of the sport with the ability to make adjustments in strategies and coaching behaviors. A comparison of the current sample of nonscholarship, small-college football players and a sample of full-scholarship (NCAA Division I-AA) football players revealed several interesting differences. In the current sample, the correlations between social support and satisfaction, and democratic behavior and satisfaction, were substantially higher. Additionally, a much stronger negative relationship existed between autocratic coaching behaviors and satisfaction among small-college players

Follow-up to strabismic training

Follow-up to strabismic trainin

Coupled opto-electronic simulation of organic bulk-heterojunction solar cells: parameter extraction and sensitivity analysis

A general problem arising in computer simulations is the number of material and device parameters, which have to be determined by dedicated experiments and simulation-based parameter extraction. In this study we analyze measurements of the short-circuit current dependence on the active layer thickness and current-voltage curves in poly(3-hexylthiophene):[6,6]-phenyl-C61-butyric acid methyl ester (P3HT:PCBM) based solar cells. We have identified a set of parameter values including dissociation parameters that describe the experimental data. The overall agreement of our model with experiment is good, however a discrepancy in the thickness dependence of the current-voltage curve questions the influence of the electric field in the dissociation process. In addition transient simulations are analyzed which show that a measurement of the turn-off photocurrent can be useful for estimating charge carrier mobilities.Comment: 10 pages, 12 figures, 2 tables, Accepted for publication in Journal of Applied Physic

From Observers to Participants: Joining the Scientific Community

In this essay, we have integrated the voices of our mentors and students to explore 45 years of undergraduate research experiences and their role in shaping our scientific community. In considering our collective experiences, we see undergraduate involvement in research as a rich source of community development, one that has both touched our lives and influenced our teaching

Rain volume estimation over areas using satellite and radar data

The analysis of 18 convective clusters demonstrates that the extension of the Area-Time-Integral (ATI) technique to the use of satellite data is possible. The differences of the internal structures of the radar reflectivity features, and of the satellite features, give rise to differences in estimating rain volumes by delineating area; however, by focusing upon the area integrated over the lifetime of the storm, it is suggested that some of the errors produced by the differences in the cloud geometries as viewed by radar or satellite are minimized. The results are good and future developments should consider data from different climatic regions and should allow for implementation of the technique in a general circulation model

Fuel treatment planning: Fragmenting high fuel load areas while maintaining availability and connectivity of faunal habitat

Reducing the fuel load in fire-prone landscapes is aimed at mitigating the risk of catastrophic wildfires but there are ecological consequences. Maintaining habitat for fauna of both sufficient extent and connectivity while fragmenting areas of high fuel loads presents land managers with seemingly contrasting objectives. Faced with this dichotomy, we propose a Mixed Integer Programming (MIP) model that can optimally schedule fuel treatments to reduce fuel hazards by fragmenting high fuel load regions while considering critical ecological requirements over time and space. The model takes into account both the frequency of fire that vegetation can tolerate and the frequency of fire necessary for fire-dependent species. Our approach also ensures that suitable alternate habitat is available and accessible to fauna affected by a treated area. More importantly, to conserve fauna the model sets a minimum acceptable target for the connectivity of habitat at any time. These factors are all included in the formulation of a model that yields a multi-period spatially-explicit schedule for treatment planning. Our approach is then demonstrated in a series of computational experiments with hypothetical landscapes, a single vegetation type and a group of faunal species with the same habitat requirements. Our experiments show that it is possible to fragment areas of high fuel loads while ensuring sufficient connectivity of habitat over both space and time. Furthermore, it is demonstrated that the habitat connectivity constraint is more effective than neighbourhood habitat constraints. This is critical for the conservation of fauna and of special concern for vulnerable or endangered species

An optimisation approach for fuel treatment planning to break the connectivity of high-risk regions

Uncontrolled wildfires can lead to loss of life and property and destruction of natural resources. At the same time, fire plays a vital role in restoring ecological balance in many ecosystems. Fuel management, or treatment planning by way of planned burning, is an important tool used in many countries where fire is a major ecosystem process. In this paper, we propose an approach to reduce the spatial connectivity of fuel hazards while still considering the ecological fire requirements of the ecosystem. A mixed integer programming (MIP) model is formulated in such a way that it breaks the connectivity of high-risk regions as a means to reduce fuel hazards in the landscape. This multi-period model tracks the age of each vegetation type and determines the optimal time and locations to conduct fuel treatments. The minimum and maximum Tolerable Fire Intervals (TFI), which define the ages at which certain vegetation type can be treated for ecological reasons, are taken into account by the model. Examples from previous work that explicitly disconnect contiguous areas of high fuel load have often been limited to using single vegetation types implemented within rectangular grids. We significantly extend such work by including modelling multiple vegetation types implemented within a polygon-based network to achieve a more realistic representation of the landscape. An analysis of the proposed approach was conducted for a fuel treatment area comprising 711 treatment units in the Barwon-Otway district of Victoria, Australia. The solution of the proposed model can be obtained for 20-year fuel treatment planning within a reasonable computation time of eight hours

Differential role of entorhinal and hippocampal nerve growth factor in short- and long-term memory modulation

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