University of Georgia

About: University of Georgia is a education organization based out in Athens, Georgia, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 41934 authors who have published 93622 publications receiving 3713212 citations. The organization is also known as: UGA & Franklin College.

A total system approach to sustainable pest management

Abstract: A fundamental shift to a total system approach for crop protection is urgently needed to resolve escalating economic and environmental consequences of combating agricultural pests. Pest management strategies have long been dominated by quests for “silver bullet” products to control pest outbreaks. However, managing undesired variables in ecosystems is similar to that for other systems, including the human body and social orders. Experience in these fields substantiates the fact that therapeutic interventions into any system are effective only for short term relief because these externalities are soon “neutralized” by countermoves within the system. Long term resolutions can be achieved only by restructuring and managing these systems in ways that maximize the array of “built-in” preventive strengths, with therapeutic tactics serving strictly as backups to these natural regulators. To date, we have failed to incorporate this basic principle into the mainstream of pest management science and continue to regress into a foot race with nature. In this report, we establish why a total system approach is essential as the guiding premise of pest management and provide arguments as to how earlier attempts for change and current mainstream initiatives generally fail to follow this principle. We then draw on emerging knowledge about multitrophic level interactions and other specific findings about management of ecosystems to propose a pivotal redirection of pest management strategies that would honor this principle and, thus, be sustainable. Finally, we discuss the potential immense benefits of such a central shift in pest management philosophy.

Appropriate Models for the Management of Infectious Diseases

Abstract: Background Mathematical models have become invaluable management tools for epidemiologists, both shedding light on the mechanisms underlying observed dynamics as well as making quantitative predictions on the effectiveness of different control measures. Here, we explain how substantial biases are introduced by two important, yet largely ignored, assumptions at the core of the vast majority of such models. Methods and Findings First, we use analytical methods to show that (i) ignoring the latent period or (ii) making the common assumption of exponentially distributed latent and infectious periods (when including the latent period) always results in underestimating the basic reproductive ratio of an infection from outbreak data. We then proceed to illustrate these points by fitting epidemic models to data from an influenza outbreak. Finally, we document how such unrealistic a priori assumptions concerning model structure give rise to systematically overoptimistic predictions on the outcome of potential management options. Conclusion This work aims to highlight that, when developing models for public health use, we need to pay careful attention to the intrinsic assumptions embedded within classical frameworks.

A second-generation linkage map of the bovine genome.

Abstract: We report a bovine linkage map constructed with 1236 polymorphic DNA markers and 14 erythrocyte antigens and serum proteins. The 2990-cM map consists of a sex-specific, X chromosome linkage group and 29 sex-averaged, autosomal linkage groups with an average interval size of 2.5 cM. The map contains 627 new markers and 623 previously linked markers, providing a basis for integrating the four published bovine maps. Orientation and chromosomal assignment of all the linkage groups, except BTA20 and BTA22, was provided by 88 markers that were assigned previously to chromosomes. This map provides sufficient marker density for genomic scans of populations segregating quantitative trait loci (QTL) and subsequent implementation of marker-assisted selection (MAS) mating schemes.

Visualizing structure and transitions in high-dimensional biological data

Abstract: The high-dimensional data created by high-throughput technologies require visualization tools that reveal data structure and patterns in an intuitive form. We present PHATE, a visualization method that captures both local and global nonlinear structure using an information-geometric distance between data points. We compare PHATE to other tools on a variety of artificial and biological datasets, and find that it consistently preserves a range of patterns in data, including continual progressions, branches and clusters, better than other tools. We define a manifold preservation metric, which we call denoised embedding manifold preservation (DEMaP), and show that PHATE produces lower-dimensional embeddings that are quantitatively better denoised as compared to existing visualization methods. An analysis of a newly generated single-cell RNA sequencing dataset on human germ-layer differentiation demonstrates how PHATE reveals unique biological insight into the main developmental branches, including identification of three previously undescribed subpopulations. We also show that PHATE is applicable to a wide variety of data types, including mass cytometry, single-cell RNA sequencing, Hi-C and gut microbiome data.

Toward a Theory-Based Measurement of Culture

Abstract: In reviewing the history of the conceptualization and measurement of “culture,” one quickly realizes that there is wide-ranging and contradictory scholarly opinion about which values, norms, and beliefs should be measured to represent the concept of “culture.” We explore an alternate theory-based view of culture via social identity theory (SIT), which suggests that each individual is influenced by plethora of cultures and sub-cultures–some ethnic, some national, and some organizational. In IS research, the culture of subjects and respondents is problematic because it is typically an overly simplistic categorization. IS research nearly always assumes that an individual living in a particular place and time belongs to a single “culture,” e.g., someone living in Egypt is automatically classified as being a member of the Egyptian culture, or, more broadly, the Arab culture. This dearth of clear concepts and measures for “culture” may explain why cross-cultural research has been so exceedingly difficult to conduct. It may also explain why it has been hard to develop and refine theories. Moreover, it may give insight into why reasonable explained variance in predictive models has not been higher. Finally, it is very possible that much cross-cultural business research could be rightly accused of advancing an “ecological fallacy” by not recognizing the individual makeup of persons with respect to culture. Using SIT (or other theory bases) as grounding for cultural research programs implies the use of certain methodological approaches. Each study would have to establish the salient “cultures” in each individual’s background and include these different “cultures” as independent variables in positivist research. In qualitative research, there would need to be an equally rigorous assessment of the cultural identifiers of each individual.