Feeding and management investigations at the United States Dairy Experiment Station at Beltsville, MD., 1930 report /

"January, 1932."

Feeding and management investigations at the United States Dairy Experiment Station at Beltsville, Md., 1932 report /

"December 1933."

List of sires proved in dairy-herd improvement associations, 1948 /

"June 1948."

List of sires proved in dairy-herd-improvement associations, 1946 /

"October 1946."

Approaches and Strategy for Cancer Research and Surveillance Data: Integration, Information Pipeline, Data Models, and Informatics Opportunities

Thesis (Ph.D.)--University of Washington, 2016-04

Selecting optimal instantiations of data models - Theory and validation of an ex ante approach

The schema of an information system can significantly impact the ability of end users to efficiently and effectively retrieve the information they need. Obtaining quickly the appropriate data increases the likelihood that an organization will make good decisions and respond adeptly to challenges. This research presents and validates a methodology for evaluating, ex ante, the relative desirability of alternative instantiations of a model of data. In contrast to prior research, each instantiation is based on a different formal theory. This research theorizes that the instantiation that yields the lowest weighted average query complexity for a representative sample of information requests is the most desirable instantiation for end-user queries. The theory was validated by an experiment that compared end-user performance using an instantiation of a data structure based on the relational model of data with performance using the corresponding instantiation of the data structure based on the object-relational model of data. Complexity was measured using three different Halstead metrics: program length, difficulty, and effort. For a representative sample of queries, the average complexity using each instantiation was calculated. As theorized, end users querying the instantiation with the lower average complexity made fewer semantic errors, i.e., were more effective at composing queries. (c) 2005 Elsevier B.V. All rights reserved.

Assessing moth migration and population structuring in Helicoverpa annigera (Lepidoptera : Noctuidae) at the regional scale: Example from the Darling Downs, Australia

Analysis of gene flow and migration of Helicoverpa armigera (Hubner) in a major cropping region of Australia identified substantial genetic structuring, migration events, and significant population genotype changes over the 38-mo sample period from November 1999 to January 2003. Five highly variable microsatellite markers were used to analyze 916 individuals from 77 collections across 10 localities in the Darling Downs. The molecular data indicate that in some years (e.g., April 2002-March 2003), low levels of H. armigera migration and high differentiation between populations occurred, whereas in other years (e.g., April 2001-March 2002), there were higher levels of adult moth movement resulting in little local structuring of populations. Analysis of populations in other Australian cropping regions provided insight into the quantity and direction of immigration of H. armigera adults into the Darling Downs growing region of Australia. These data provide evidence adult moth movement differs from season to season, highlighting the importance of studies in groups such as the Lepidoptera extending over consecutive years, because short-term sampling may be misleading when population dynamics and migration change so significantly. This research demonstrates the importance of maintaining a coordinated insecticide resistance management strategy, because in some years H. armigera populations may be independent within a region and thus significantly influenced by local management practices; however, periods with high migration will occur and resistance may rapidly spread.

An Incremental EM-based Learning Approach for On-Line Prediction of Hospital Resource Utilization

Objective: Inpatient length of stay (LOS) is an important measure of hospital activity, health care resource consumption, and patient acuity. This research work aims at developing an incremental expectation maximization (EM) based learning approach on mixture of experts (ME) system for on-line prediction of LOS. The use of a batchmode learning process in most existing artificial neural networks to predict LOS is unrealistic, as the data become available over time and their pattern change dynamically. In contrast, an on-line process is capable of providing an output whenever a new datum becomes available. This on-the-spot information is therefore more useful and practical for making decisions, especially when one deals with a tremendous amount of data. Methods and material: The proposed approach is illustrated using a real example of gastroenteritis LOS data. The data set was extracted from a retrospective cohort study on all infants born in 1995-1997 and their subsequent admissions for gastroenteritis. The total number of admissions in this data set was n = 692. Linked hospitalization records of the cohort were retrieved retrospectively to derive the outcome measure, patient demographics, and associated co-morbidities information. A comparative study of the incremental learning and the batch-mode learning algorithms is considered. The performances of the learning algorithms are compared based on the mean absolute difference (MAD) between the predictions and the actual LOS, and the proportion of predictions with MAD < 1 day (Prop(MAD < 1)). The significance of the comparison is assessed through a regression analysis. Results: The incremental learning algorithm provides better on-line prediction of LOS when the system has gained sufficient training from more examples (MAD = 1.77 days and Prop(MAD < 1) = 54.3%), compared to that using the batch-mode learning. The regression analysis indicates a significant decrease of MAD (p-value = 0.063) and a significant (p-value = 0.044) increase of Prop(MAD

Long-term persistence of multi-drug-resistant Salmonella enterica serovar Newport in two dairy herds

Objective - To evaluate the association between maintaining joint hospital and maternity pens;and persistence of multi-drug-resistant (MDR) Salmonella enterica serovar Newport on 2 dairy farms. Design - Observational study. Sample Population - Feces and environmental samples from 2 dairy herds. Procedure - Herds were monitored for fecal shedding of S enterica Newport after outbreaks of clinical disease. Fecal and environmental samples were collected approximately monthly from pens housing sick cows and calving cows and from pens containing lactating cows. Cattle shedding the organism were tested serially on subsequent visits to determine carrier status. One farm was resampled after initiation of interventional procedures, including separation of hospital and maternity pens. Isolates were characterized via serotyping, determination of antimicrobial resistance phenotype, detection of the CMY-2 gene, and DNA fingerprinting. Results - The prevalence (32.4% and 33.3% on farms A and B, respectively) of isolating Salmonella from samples from joint hospital-maternity pens was significantly higher than the prevalence in samples from pens housing preparturient cows (0.8%, both farms) and postparturient cows on Farm B (8.8%). Multi-drug-resistant Salmonella Newport was isolated in high numbers from bedding material, feed refusals, lagoon slurry, and milk filters. One cow excreted the organism for 190 days. Interventional procedures yielded significant reductions in the prevalences of isolating the organism from fecal and environmental samples. Most isolates were of the C2 serogroup and were resistant to third-generation cephalosporins. Conclusions and Clinical Relevance - Management practices may be effective at reducing the persistence of MDR Salmonella spp in dairy herds, thus mitigating animal and public health risk.

Socioeconomic disadvantage and changes in health risk behaviours in Australia: 1989-90 to 2001

Objective. Lower socioeconomic status (SES) is associated in industrialized countries with unhealthy lifestyle characteristics, such as smoking, physical inactivity and being overweight or obese. This paper examines changes over time in the association between SES and smoking status, physical activity and being overweight or obese in Australia. Methods. Data were taken from three successive national health surveys in Australia carried out in 1989-90 (n = 54 576), 1995 (n = 53 828) and 2001 (n = 26 863). Participants in these surveys were selected using a national probability sampling strategy, and aggregated data for geographical areas are used to determine the changing association between SES and lifestyle over time. Findings. Overall, men had less healthy lifestyles, In 2001 inverse SES trends for both men and women showed that those living in lower SES areas were more likely to smoke and to be sedentary and obese, There were some important socioeconomic changes over the period 1989-90 to 2001. The least socioeconomically disadvantaged areas had the largest decrease in the percentage of people smoking tobacco (24% decrease for men and 12% for women) and the largest decrease in the percentage of people reporting sedentary activity levels (25% decrease for men and 22% for women). While there has been a general increase in the percentage over time of those who are overweight or obese, there is a modest trend for being overweight to have increased (by about 16% only among females) among those living in areas of higher SES. Conclusion. Socioeconomic inequalities have been increasing for several key risk behaviours related to health; this suggests that T specific population-based prevention strategies intended to reduce health inequalities are needed.

Assessing the quality of risk factor survey data: lessons from the WHO MONICA Project

Background and purpose Survey data quality is a combination of the representativeness of the sample, the accuracy and precision of measurements, data processing and management with several subcomponents in each. The purpose of this paper is to show how, in the final risk factor surveys of the WHO MONICA Project, information on data quality were obtained, quantified, and used in the analysis. Methods and results In the WHO MONICA (Multinational MONItoring of trends and determinants in CArdiovascular disease) Project, the information about the data quality components was documented in retrospective quality assessment reports. On the basis of the documented information and the survey data, the quality of each data component was assessed and summarized using quality scores. The quality scores were used in sensitivity testing of the results both by excluding populations with low quality scores and by weighting the data by its quality scores. Conclusions Detailed documentation of all survey procedures with standardized protocols, training, and quality control are steps towards optimizing data quality. Quantifying data quality is a further step. Methods used in the WHO MONICA Project could be adopted to improve quality in other health surveys.