Proceedings of the 23rd annual Central Plains irrigation conference

Presented at Proceedings of the 23rd annual Central Plains irrigation conference held in Burlington, Colorado on February 22-23, 2011.Includes bibliographical references

The Determination of Technology and Commodity Policy in the U.S. Dairy Industry

United States dairy policy includes both predatory and productive components. The milk price support program is designed to transfer income to dairy farmers while research and extension expenditures are designed to increase social welfare. The purpose of this chapter is to provide an empirical example of the theory developed in the previous chapter. It has long been recognized the government research and extension policies have been significant contributors to technological advance in agriculture (Evenson and Kislev 1976, Evenson, Waggoner, and Ruttan 1979). The advent of technological change on agriculture and its policy implications was first noted by Schultz (1945, 1953). Some, like Cochrane (1958) in characterizing his famous technological treadmill thesis, argued for price supports in order to compensate farmers for the adverse effects of research on farmers\u27 welfare. Indeed, commentators like Thurow (1981) and Schlesinger (1984) argue that public good provision in agriculture is one of the few major economic success stories of government intervention in the history of the United States. Nevertheless, one of the most stylized facts in government policy intervention in agriculture is the pervasive level and overwhelming evidence of underinvestment in public research (Ruttan 1982). Concomitant to this notion, economists have alleged that governments \u27overinvest\u27 in commodity policies because of the associated deadweight losses generated

Probabilistic abstract interpretation: From trace semantics to DTMC’s and linear regression

In order to perform probabilistic program analysis we need to consider probabilistic languages or languages with a probabilistic semantics, as well as a corresponding framework for the analysis which is able to accommodate probabilistic properties and properties of probabilistic computations. To this purpose we investigate the relationship between three different types of probabilistic semantics for a core imperative language, namely Kozen’s Fixpoint Semantics, our Linear Operator Semantics and probabilistic versions of Maximal Trace Semantics. We also discuss the relationship between Probabilistic Abstract Interpretation (PAI) and statistical or linear regression analysis. While classical Abstract Interpretation, based on Galois connection, allows only for worst-case analyses, the use of the Moore-Penrose pseudo inverse in PAI opens the possibility of exploiting statistical and noisy observations in order to analyse and identify various system properties

Efficient CSL Model Checking Using Stratification

For continuous-time Markov chains, the model-checking problem with respect to continuous-time stochastic logic (CSL) has been introduced and shown to be decidable by Aziz, Sanwal, Singhal and Brayton in 1996. Their proof can be turned into an approximation algorithm with worse than exponential complexity. In 2000, Baier, Haverkort, Hermanns and Katoen presented an efficient polynomial-time approximation algorithm for the sublogic in which only binary until is allowed. In this paper, we propose such an efficient polynomial-time approximation algorithm for full CSL. The key to our method is the notion of stratified CTMCs with respect to the CSL property to be checked. On a stratified CTMC, the probability to satisfy a CSL path formula can be approximated by a transient analysis in polynomial time (using uniformization). We present a measure-preserving, linear-time and -space transformation of any CTMC into an equivalent, stratified one. This makes the present work the centerpiece of a broadly applicable full CSL model checker. Recently, the decision algorithm by Aziz et al. was shown to work only for stratified CTMCs. As an additional contribution, our measure-preserving transformation can be used to ensure the decidability for general CTMCs.Comment: 18 pages, preprint for LMCS. An extended abstract appeared in ICALP 201

Prescribed fire effects on resource selection by cattle in mesic sagebrush steppe. Part 1: Spring grazing

Prescribed fire is commonly applied world-wide as a tool for enhancing habitats and altering resource-selection patterns of grazing animals. A scientific basis for this practice has been established in some ecosystems but its efficacy has not been rigorously evaluated on mesic sagebrush steppe. Beginning in 2003, resource-selection patterns of beef cows were investigated using global positioning system (GPS) collars for 2 years before and for 5 years after a fall prescribed burn was applied to mesic sagebrush steppe in the Owyhee Mountains of southwestern Idaho, USA. Resource-selection functions (RSF) developed from these data indicated cattle selected for lightly to moderately burned areas for all 5 postfire years. Cattle had been neutral towards these areas prior to the fire when their distribution was primarily affected by slope, sagebrush dominance, and distance to upland water. Resource-selection responses to the fire lasted 2-3 years longer than would be expected for fire-induced, forage-quality improvement effects. Although this is a case study and caution should be taken in extrapolating these results, if applied under conditions similar to this study, livestock producers and natural resource managers can likely use fall prescribed fire in the mesic sagebrush steppe to affect cattle resource-use patterns for 5 years postfire.KEYWORDS: Modeling, Livestock distribution, Habitat use, GPS tracking, Burning, Rangeland improvementThis is the publisher’s final pdf. The published article is copyrighted by Elsevier and can be found at: http://www.journals.elsevier.com/journal-of-arid-environments

Uncovering precision phenotype-biomarker associations in traumatic brain injury using topological data analysis

Background: Traumatic brain injury (TBI) is a complex disorder that is traditionally stratified based on clinical signs and symptoms. Recent imaging and molecular biomarker innovations provide unprecedented opportunities for improved TBI precision medicine, incorporating patho-anatomical and molecular mechanisms. Complete integration of these diverse data for TBI diagnosis and patient stratification remains an unmet challenge. Methods and findings: The Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) Pilot multicenter study enrolled 586 acute TBI patients and collected diverse common data elements (TBI-CDEs) across the study population, including imaging, genetics, and clinical outcomes. We then applied topology-based data-driven discovery to identify natural subgroups of patients, based on the TBI-CDEs collected. Our hypothesis was two-fold: 1) A machine learning tool known as topological data analysis (TDA) would reveal data-driven patterns in patient outcomes to identify candidate biomarkers of recovery, and 2) TDA-identified biomarkers would significantly predict patient outcome recovery after TBI using more traditional methods of univariate statistical tests. TDA algorithms organized and mapped the data of TBI patients in multidimensional space, identifying a subset of mild TBI patients with a specific multivariate phenotype associated with unfavorable outcome at 3 and 6 months after injury. Further analyses revealed that this patient subset had high rates of post-traumatic stress disorder (PTSD), and enrichment in several distinct genetic polymorphisms associated with cellular responses to stress and DNA damage (PARP1), and in striatal dopamine processing (ANKK1, COMT, DRD2). Conclusions: TDA identified a unique diagnostic subgroup of patients with unfavorable outcome after mild TBI that were significantly predicted by the presence of specific genetic polymorphisms. Machine learning methods such as TDA may provide a robust method for patient stratification and treatment planning targeting identified biomarkers in future clinical trials in TBI patients

Structural changes in commercial agriculture

The basic idea of the conference on Structural Changes in Commercial Agriculture was planted in the spring of 1964 by Earl 0. Heady. He outlined for the North Central Farm Management Research Committee his concern about the kind and amount of response to both current and prospective structural changes in the commercial farm firm. Many changes represent adjustments to technological and other innovations originating in marketing, research, and educational agencies serving farmers.https://lib.dr.iastate.edu/card_reports/1025/thumbnail.jp

Consumer behaviour and the life-course: shopper reactions to self service grocery shops and supermarkets in England c.1947-1975

This is the author accepted manuscript. The final version is available from SAGE Publications via the DOI in this recordThe paper examines the development of self-service grocery shopping from a consumer perspective. Using qualitative data constructed through a nationwide biographical survey and oral histories, it is possible to go beyond contemporary market surveys which give insufficient attention to shopping as a socially and culturally embedded practice. The paper uses the conceptual framework of the life-course, to demonstrate how grocery shopping is a complex activity, in which the retail encounter is shaped by the specific interconnection of different retail formats with consumer characteristics and situational influences. Consumer reactions to retail modernization must be understood in relation to the development of consumer practices at points of transition and stability within the life-course. These practices are accessed by examining retrospective consumer narratives about food shopping

Statins and Physical Activity in Older Men: The Osteoporotic Fractures in Men Study

IMPORTANCE: Muscle pain, fatigue, and weakness are common adverse effects of statin medications and may decrease physical activity in older men. OBJECTIVE: Determine whether statin use is associated with physical activity, longitudinally and cross-sectionally. DESIGN, SETTING, AND PARTICIPANTS: Men participating in the Osteoporotic Fractures in Men Study, a multicenter prospective cohort study of community-living men age 65+, enrolled between March 2000-April 2002. EXPOSURE: Statin use as determined by an inventory of medications (taken within last 30 days). In cross-sectional analyses, statin use categories were: users and nonusers. In longitudinal analyses, categories were: prevalent users (baseline use and throughout study), new users (initiated use during the study) and nonusers (never used). MAIN OUTCOMES AND MEASURE: Self-reported physical activity at baseline and 2 follow-up visits using the Physical Activity Scale for the Elderly (PASE). At the third visit, an accelerometer measured metabolic equivalents (METs; kcal/kg/hr) and minutes of moderate activity (METs ≥3.0), vigorous activity (METs ≥6.0), and sedentary behavior (METs ≤1.5). RESULTS: At baseline, 989 men (24%) were users and 3,148 (76%) were nonusers. The adjusted difference in baseline PASE between users and nonusers was -5.8 points (95% CI, -10.9 to -0.7). A total of 3,039 men met the inclusion criteria for longitudinal analysis: 727 (24%) prevalent users, 845 (28%) new users, 1,467 (48%) nonusers. PASE declined by an average of 2.5 points/year (2.0-3.0) for nonusers and 2.8 points/year (2.1, 3.5) for prevalent users, a nonstatistical difference (0.3 point, -0.5-1). For new users, annual PASE score declined at a faster rate than nonusers (0.9 point difference; 0.1-1.7). 3,071 men had adequate accelerometry data, 1,542 (50%) were statin users. Statin users expended less METS (0.03 kcal/kg/hr less; 0.02-0.04); engaged in less moderate physical activity (5.4 fewer minutes/day; 1.9-8.8), less vigorous activity (0.6 fewer minutes/day; 0.1-1.1), and more sedentary behavior (7.6 greater minutes/day; 2.6-12.4). CONCLUSION AND RELEVANCE: Statin use was associated with modestly lower physical activity among community-living men, even after accounting for medical history and other potentially confounding factors. The clinical significance of these findings deserves further investigation