The relationship between measurement uncertainty and reporting interval

Background Measurement uncertainty (MU) estimates can be used by clinicians in result interpretation for diagnosis and monitoring and by laboratories in assessing assay fitness for use and analytical troubleshooting. However, MU is not routinely used to assess the appropriateness of the analyte reporting interval. We describe the relationship between MU and the analyte reporting interval. Methods and results The reporting interval R is the smallest unit of measurement chosen for clinical reporting. When choosing the appropriate value for R, it is necessary that the reference change values and expanded MU values can be meaningfully calculated. Expanded MU provides the tighter criterion for defining an upper limit for R. This limit can be determined as R ≤  k·SDa/1.9, where SDa is the analytical standard deviation and k is the coverage factor (usually 2). Conclusion Using MU estimates to determine the reporting interval for quantitative laboratory results ensures that reporting practices match local analytical performance and recognizes the inherent error of the measurement process. </jats:sec

Bootstrap methods for the empirical study of decision-making and information flows in social systems

Abstract: We characterize the statistical bootstrap for the estimation of information theoretic quantities from data, with particular reference to its use in the study of large-scale social phenomena. Our methods allow one to preserve, approximately, the underlying axiomatic relationships of information theory—in particular, consistency under arbitrary coarse-graining—that motivate use of these quantities in the first place, while providing reliability comparable to the state of the art for Bayesian estimators. We show how information-theoretic quantities allow for rigorous empirical study of the decision-making capacities of rational agents, and the time-asymmetric flows of information in distributed systems. We provide illustrative examples by reference to ongoing collaborative work on the semantic structure of the British Criminal Court system and the conflict dynamics of the contemporary Afghanistan insurgency

The Science of Learning: Understanding the Learning Process and its Implementation into the Classroom

College and higher education is often seen as the next step for many students pursuing a particular career or field. These institutions strive to facilitate learning and maintain a rewarding academic environment. However, students often face various challenges when first attending college which is reflected by high levels of dropout and withdrawal from general education courses, especially for first-time students. In fact, according to the education data initiation, “at 4-year institutions, 18.4% of first-time, full-time college freshmen dropped out between 2019 and 2020” (Hansen & Checked, 2022). One of these challenges is understanding the process of learning on a fundamental level. If more students had knowledge of how this process worked, it would lead to better habits of how they should learn the material and content, allowing students to have more success in their courses even among different subjects

Reputational Review I: Expertise, Bias and Delay

Expertise, bias and delay arguments are shifting the focus of judicial review from the legality of administrative decisions to the reputation of administrative decision- makers. These grounds measure the skill, objectivity and efficiency characteristics that define administrators\u27 reputations. They make it possible for courts to consider these reputations, even if only by way of unarticulated judicial notice, when deciding judicial review applications. After setting out the theory of expertise, bias and delay implicit in recent Supreme Court of Canada decisions, the author concludes that courts must use less impressionistic measures in judging these concepts, lawyers must present more concrete reputational evidence in arguing them, and administrators must become more sensitive to their impact on public opinion

Development of smart bio-polymeric nanostructures for stimuli-response based applications

Biodegradable polymers are a rising commodity in the polymer industry, offering a resolution to disposal and environmental concerns. Biocompatibility within these types of polymers has resulted in extensive research towards medical applications. This research explores the development of smart bio-polymeric nanostructures by a low-cost manufacturing process known as electrospinning. Specific polymers were selected for this work to provide a stimuli-responsive system that is applicable for a range of applications

From Self-Sufficiency to Personal and Family Sustainability: A New Paradigm for Social Policy

Current social policy that affects welfare recipients focuses on the concept of self-sufficiency where leaving welfare for work is the goal. While this approach has reduced welfare rolls, it has not necessarily helped low-income people improve their economic, educational, or social outlook. This paper suggests that the concept of Personal and Family Sustainability (PFS) may be a better way to evaluate and direct social policy. A definition of PFS is developed from the environmental and community development roots of sustainability and four domains for creating PFS indicators are introduced