MANAGEMENT OF INTENSIVE FORAGE-BEEF PRODUCTION UNDER YIELD UNCERTAINTY

Forage production variability is incorporated into a decision theory framework for a beef producer in East Texas. The results suggest that the least risky, and also the most profitable, approach to intensive forage beef production is to plan for relatively poor weather conditions and low forage production. This results in a more diverse forage system and a smaller herd size than would be found optimal under the assumption of constant average forage production. These results also demonstrate that the assumption of constant average forage production may results in grossly exaggerated estimates of expected net returns.Livestock Production/Industries, Risk and Uncertainty,

OPTIMAL STOCKING OF RANGELAND FOR LIVESTOCK PRODUCTION WITHIN A DYNAMIC FRAMEWORK

A dynamic model is constructed and utilized to illustrate the interactions of several primary dynamic ecologic and economic relationships that are important in effective rangeland management. Within this context, the implications of various range management strategies are explored.Livestock Production/Industries,

Unlocking the Secrets of Ancient Writing. The Parallel Lives of Michael Ventris and Linda Schele and the Decipherment of Mycenaean and Mayan Writing

Catalogue of an exhibition conducted in conjunction with the Eleventh International Mycenological Colloquium held at the University of Texas at Austin in 2000. This program features brief histories of the CIPEM Mycenological conferences and PASP, followed by comparative retrospectives on both Michael Ventris, who deciphered Linear B, and Linda Schele, who performed a similar feat for Mayan glyphs.Classic

The dynamics of crop yields in the U. S. Corn Belt as effected by weather and technological progress

Producers of agricultural products, policy makers, and consumers alike have a keen interest in what will happen to crop yields in the future. This study attempts to carefully analyze past trends in crop yields in five Corn Belt states, Illinois, Indiana, Iowa, Missouri, and Ohio, and how they have been affected by weather and technological progress over time;State average yields for corn grain, corn silage, soybeans, small grains, and meadow (leguminous hay) are modeled as a system of equations where yields are functions of weather, technological progress, and nitrogen application. Time series data on yields, nitrogen and corn prices, nitrogen application, and weather are collected. Time is used as a proxy variable for technological progress and the models from all five states are estimated using three stage least squares regression. The estimated models do a good job of fitting the 1951-1980 time series data and they illustrate that technological progress and weather are the most important factors that affect yields;The prospects of favorable future weather are analyzed by regressing weather variables from 1930-1980 or dummy variables for each state and for periods of abnormally favorable weather. These models are able to explain only a small portion of the total variance in weather, but they do indicate that the periods during 1942-1952 and 1961-1973 can be characterized as more cool and wet, and generally more favorable to crop yields than average. However, attempts to use this information to project future weather would be ludicrous;The prospects of future yield increases as a result of technological progress are examined by looking at some of the major factors that affect crop yields. It can be seen that technological progress is a large and complex set of interacting conditions, occurrences and activities that cannot be easily modeled, described, or projected. Attempts to project future yields must be based on various assumptions about future technological progress;Yields are projected for the year 2000, using the estimated models, under six different scenarios based on various assumptions about future technological progress, weather, and nitrogen application. In general, with the noted exception of wheat, there is little evidence found in the time series data that would indicate a leveling off of Corn Belt crop yields in the near future

Discrete event simulation Model of the Ground Maintenance Operations Cycle of a Reusable Launch Vehicle

The Air Force uses a family of expendable launch vehicles to meet its spacelift needs. Unfortunately, this method is not responsive: months of preparation are typically required and launch costs are high. Consequently, the Air Force seeks a reusable military launch vehicle that can be launched inexpensively and quickly regenerated between flights. Air Force Research Laboratory personnel desire a tool to help evaluate candidate designs and perform tradeoff studies necessary to acquire a launch vehicle that will achieve Air Force goals. The objective of this research was first to develop a conceptual model of maintenance operations needed to regenerate a launch vehicle between flights, and then to translate this conceptual model into a discrete event simulation tool. This research was accomplished concurrently with Stiegelmeier, who focused on vehicle prelaunch operations

Recreation Embedded State Tuning for Optimal Readiness and Effectiveness (RESTORE)

Physiological self-regulation training is a behavioral medicine intervention that has demonstrated capability to improve psychophysiological coping responses to stressful experiences and to foster optimal behavioral and cognitive performance. Once developed, these psychophysiological skills require regular practice for maintenance. A concomitant benefit of these physiologically monitored practice sessions is the opportunity to track crew psychophysiological responses to the challenges of the practice task in order to detect shifts in adaptability that may foretell performance degradation. Long-duration missions will include crew recreation periods that will afford physiological self-regulation training opportunities. However, to promote adherence to the regimen, the practice experience that occupies their recreation time must be perceived by the crew as engaging and entertaining throughout repeated reinforcement sessions on long-duration missions. NASA biocybernetic technologies and publications have developed a closed-loop concept that involves adjusting or modulating (cybernetic, for governing) a person's task environment based upon a comparison of that person's physiological responses (bio-) with a training or performance criterion. This approach affords the opportunity to deliver physiological self-regulation training in an entertaining and motivating fashion and can also be employed to create a conditioned association between effective performance state and task execution behaviors, while enabling tracking of individuals psychophysiological status over time in the context of an interactive task challenge. This paper describes the aerospace spin-off technologies in this training application area as well as the current spin-back application of the technologies to long-duration missions - the Recreation Embedded State Tuning for Optimal Readiness and Effectiveness (RESTORE) concept. The RESTORE technology is designed to provide a physiological self-regulation training countermeasure for maintaining and reinforcing cognitive readiness, resilience under psychological stress, and effective mood states in long-duration crews. The technology consists of a system for delivering physiological self-regulation training and for tracking crew central and autonomic nervous system function; the system interface is designed to be experienced as engaging and entertaining throughout repeated training sessions on long-duration missions. Consequently, this self-management technology has threefold capability for recreation, behavioral health problem prophylaxis and remediation, and psychophysiological assay. The RESTORE concept aims to reduce the risk of future manned exploration missions by enhancing the capability of individual crewmembers to self-regulate cognitive states through recreation-embedded training protocols to effectively deal with the psychological toll of long-duration space flight

Project VALHALLA

Project VALHALLA (Vertical Air Lifted High Altitude Light Launch Apparatus) is a high altitude launch platform with the objective of providing a cost efficient option for collegiate rocket organizations to perform high altitude research. This project primarily consists of a platform that will be lifted to 100,000 feet using several clusters of high altitude balloons that will be inflated using Helium. From 100,000 feet, the rocket will be launched and the platform will then descend to the ground by retrieving the helium and absorbing it back into storage tanks while pressurizing it. Currently, the project is on phase two which is prototyping and testing of various systems prior to implementing those systems in a Mk.0 build. This involves using simulation programs such as Ansys to test how air will flow around the structure and visualize the structural strains on the platform. This phase is expected to last through the 2019-2020 academic year and will allow the team to begin building the Mk.0 system in Fall 2020

Computer modeling the fatigue crack growth rate behavior of metals in corrosive environments

The objective of this task was to develop a method to digitize FCP (fatigue crack propagation) kinetics data, generally presented in terms of extensive da/dN-Delta K pairs, to produce a file for subsequent linear superposition or curve-fitting analysis. The method that was developed is specific to the Numonics 2400 Digitablet and is comparable to commercially available software products as Digimatic(sup TM 4). Experiments demonstrated that the errors introduced by the photocopying of literature data, and digitization, are small compared to those inherent in laboratory methods to characterize FCP in benign and aggressive environments. The digitizing procedure was employed to obtain fifteen crack growth rate data sets for several aerospace alloys in aggressive environments

Method and Apparatus for Performance Optimization Through Physical Perturbation of Task Elements

The invention is an apparatus and method of biofeedback training for attaining a physiological state optimally consistent with the successful performance of a task, wherein the probability of successfully completing the task is made is inversely proportional to a physiological difference value, computed as the absolute value of the difference between at least one physiological signal optimally consistent with the successful performance of the task and at least one corresponding measured physiological signal of a trainee performing the task. The probability of successfully completing the task is made inversely proportional to the physiological difference value by making one or more measurable physical attributes of the environment in which the task is performed, and upon which completion of the task depends, vary in inverse proportion to the physiological difference value