PRODUCTION ORGANIZATION IMPLICATIONS OF AGRICULTURAL INDUSTRIALIZATION

Production Economics,

A DRY MATTER QUALITY APPROACH TO PLANNING FORAGE-BEEF SYSTEMS

Livestock Production/Industries,

ON PART-TIME FARMING

Farm Management,

Some Statistical Characteristics of Part-Time Beef Farming in the South

"September 1975.

FARM GROWTH AND ESTATE TRANSFER IN AN UNCERTAIN ENVIRONMENT

Farm Management,

Potential Long-Run Adjustments for Oklahoma Panhandle Farms

The Oklahoma Agricultural Experiment Station periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311

Application of game theory models to decisions on farm practices and resource use

The use of alternative decision models for farmer decision-making under uncertainty is demonstrated in this study. Particular emphasis is given to game theoretic models. These models have previously had little empirical application to farmer decision problems. This study has shown, however, that the models suggest plans which farmers in various problem settings may wish to follow. Research and extension personnel may want to use the models to derive farmer recommendations. Farmers must make decisions in their given, uncertain environment. How are these decisions to be made so that the plans resulting will, as nearly as possible, have the outcomes desired by the farmer? This question expresses the problem this study was designed to investigate. Farmers can follow any of several models specifying how to plan under uncertainty. They may apply the models to their own problems directly or follow recommendations based on the models. Research and extension personnel influence choice of decision models through data and recommendations. Research workers must use some choice mechanism to derive recommendations. Published data may influence choice of decision models, by being suitable for use in only one or a few models. Farmers\u27 abilities to plan rationally may be increased by providing a variety of recommendations based on different decision models giving plans with outcomes desired by farmers. Abilities also may be increased by providing data applicable to several decision models

Short-Run Adjustment Opportunities for Oklahoma Panhandle Farmers

The Oklahoma Agricultural Experiment Station periodically issues revisions to its publications. The most current edition is made available. For access to an earlier edition, if available for this title, please contact the Oklahoma State University Library Archives by email at [email protected] or by phone at 405-744-6311

A blind detection of a large, complex, Sunyaev--Zel'dovich structure

We present an interesting Sunyaev-Zel'dovich (SZ) detection in the first of the Arcminute Microkelvin Imager (AMI) 'blind', degree-square fields to have been observed down to our target sensitivity of 100{\mu}Jy/beam. In follow-up deep pointed observations the SZ effect is detected with a maximum peak decrement greater than 8 \times the thermal noise. No corresponding emission is visible in the ROSAT all-sky X-ray survey and no cluster is evident in the Palomar all-sky optical survey. Compared with existing SZ images of distant clusters, the extent is large (\approx 10') and complex; our analysis favours a model containing two clusters rather than a single cluster. Our Bayesian analysis is currently limited to modelling each cluster with an ellipsoidal or spherical beta-model, which do not do justice to this decrement. Fitting an ellipsoid to the deeper candidate we find the following. (a) Assuming that the Evrard et al. (2002) approximation to Press & Schechter (1974) correctly gives the number density of clusters as a function of mass and redshift, then, in the search area, the formal Bayesian probability ratio of the AMI detection of this cluster is 7.9 \times 10^4:1; alternatively assuming Jenkins et al. (2001) as the true prior, the formal Bayesian probability ratio of detection is 2.1 \times 10^5:1. (b) The cluster mass is MT,200 = 5.5+1.2\times 10^14h-1M\odot. (c) Abandoning a physical model with num- -1.3 70 ber density prior and instead simply modelling the SZ decrement using a phenomenological {\beta}-model of temperature decrement as a function of angular distance, we find a central SZ temperature decrement of -295+36 {\mu}K - this allows for CMB primary anisotropies, receiver -15 noise and radio sources. We are unsure if the cluster system we observe is a merging system or two separate clusters.Comment: accepted MNRAS. 12 pages, 9 figure

Low back pain status in elite and semi-elite Australian football codes: a cross-sectional survey of football (soccer), Australian rules, rugby league, rugby union and non-athletic controls

<p>Abstract</p> <p>Background</p> <p>Our understanding of the effects of football code participation on low back pain (LBP) is limited. It is unclear whether LBP is more prevalent in athletic populations or differs between levels of competition. Thus it was the aim of this study to document and compare the prevalence, intensity, quality and frequency of LBP between elite and semi-elite male Australian football code participants and a non-athletic group.</p> <p>Methods</p> <p>A cross-sectional survey of elite and semi-elite male Australian football code participants and a non-athletic group was performed. Participants completed a self-reported questionnaire incorporating the Quadruple Visual Analogue Scale (QVAS) and McGill Pain Questionnaire (short form) (MPQ-SF), along with additional questions adapted from an Australian epidemiological study. Respondents were 271 elite players (mean age 23.3, range 17–39), 360 semi-elite players (mean age 23.8, range 16–46) and 148 non-athletic controls (mean age 23.9, range 18–39).</p> <p>Results</p> <p>Groups were matched for age (p = 0.42) and experienced the same age of first onset LBP (p = 0.40). A significant linear increase in LBP from the non-athletic group, to the semi-elite and elite groups for the QVAS and the MPQ-SF was evident (p < 0.001). Elite subjects were more likely to experience more frequent (daily or weekly OR 1.77, 95% CI 1.29–2.42) and severe LBP (discomforting and greater OR 1.75, 95% CI 1.29–2.38).</p> <p>Conclusion</p> <p>Foolers in Australia have significantly more severe and frequent LBP than a non-athletic group and this escalates with level of competition.</p