1,458 research outputs found

    Research Odyssey: Notes on Juvenile Delinquency in the States

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    Presently, juvenile justice is widely acknowledged as being in a state of flux in the United States. The early 1990s saw the most substantial rise in violent crime committed by juveniles ever experienced in this country. On the heels of decades of skepticism about the effectiveness of parens patriae (the state as parent), this rise was the proof for many experts who believe that the juvenile justice system should be abolished. These skeptics reason that one criminal court could still have some latitude when sentencing younger offenders, but that kids are now committing adult crimes, so it is time to treat them as adults

    Mapping the Nephron Exercise Incorporates Multiple Learning Strategies

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    Introduction: Understanding the location and action of nephron transporters and channels is important to the understanding of renal function. As each region of the nephron is unique in its inclusion of specific transporters and channels, mapping of the nephron is an effective first step in understanding overall nephron processing. We describe a small-group, active-learning exercise that facilitates students' ability to understand renal processing within each region of the nephron. Methods: Following an overview lecture on renal transporters and channels, small groups of students worked cooperatively to map the nephron. This 2-hour, collaborative exercise was developed to reinforce key concepts in renal processing of ions and nutrients and, at the same time, utilize effective learning strategies. Learning strategies incorporated in this exercise include small-group collaboration, peer teaching, retrieval practice using an audience response system, and elaboration through discussion. Results: Written examination was used to assess student understanding. Students demonstrated higher performance on a subset of questions related to this learning activity compared to the overall exam. Highly positive feedback was provided by a convenience sample of students completing an anonymous survey. Discussion: This nephron-mapping exercise was an effective means to promote synthesis and analysis of lecture content and engage students in methods that enhance learning

    Application of Structured Decision Making to Wildlife Management in Montana

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    Good decision-making is essential to conserving wildlife populations. Whereas there may be multiple ways to address a problem, perfect solutions rarely exist. Managers are therefore tasked with identifying optimal decisions that will best achieve desired outcomes. Structured decision making (SDM) is a method of decision analysis used to identify the most effective, efficient, and realistic optimal decisions while accounting for values and priorities of the decision maker. The stepwise process includes identifying the management problem, defining objectives for solving the problem, developing alternative approaches to achieve the objectives, and formally evaluating which alternative is most likely to accomplish the objectives. The SDM process can be more effective than informal decision-making because it provides a transparent way to quantitatively evaluate decisions for addressing multiple management objectives while incorporating science, uncertainty, and risk tolerance. We illustrate the application of this process to management needs, including an SDM-based decision tool developed to identify optimal decisions for proactively managing risk of pneumonia epizootics in bighorn sheep (Ovis canadensis). Pneumonia epizootics are a major challenge for managers, including in terms of knowing how or when to manage risk. The decision tool facilitates analysis of alternative decisions for how to manage herds based on predictions from a risk model, herd-specific objectives, and predicted costs and benefits of each alternative. Managers can be confident resulting decisions are most effective, efficient, and realistic because they explicitly account for important considerations managers implicitly weigh when making decisions, including competing management objectives, uncertainty in potential outcomes and risk tolerance

    Proactive Management of Pneumonia Epizootics in Bighorn Sheep in Montana—Project Update

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    Pneumonia epizootics are a major challenge for effective management of bighorn sheep (Ovis canadensis). Approximately half of the herds in Montana have suffered die-offs since the 1980s, many of which were pneumonia events. A set of models that identify risk of pneumonia and the best management decisions given that risk would be of great value for proactive management of pneumonia epizootics. Our first objective is to design and test a risk model that will help predict a herd’s risk of pneumonia. We hypothesize that various factors increase risk through pathogen exposure, pathogen spread, and disease susceptibility. Analysis of these factors comparing herds with and without recent pneumonia histories using Bayesian logistic regression will allow us to design a risk model. Our second objective is to develop a proactive decision model that incorporates estimates of pneumonia risk to help evaluate costs and benefits of alternative proactive actions appropriate to those estimates. We will use a Structured Decision Making framework, which provides a deliberative, transparent, and defensible decision-making process that is particularly valuable in complex decision-making environments such as wildlife disease management. Together the resulting risk and decision models, to be completed this year, will help managers estimate pneumonia risk and identify the best management action based on both the severity of each herd’s predicted risk and costs and benefits of competing management alternatives. Ultimately, this project will demonstrate the development and application of risk and decision models for proactive wildlife health programs in Montana Fish, Wildlife and Parks

    Physicomechanical properties of a zinc-reinforced glass ionomer restorative material

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    We compared a zinc-reinforced glass ionomer restorative material (ChemFil Rock) with three commercially available glass ionomer cements (GICs), namely, Fuji IX GP Extra, Ketac Molar Quick Aplicap, and EQUIA Fil, with respect to fracture toughness, microhardness, roughness, and abrasive wear. Fracture toughness (KIC) was tested according to ISO 13586 (n = 10). Hardness, roughness, and abrasive wear were also tested (n = 9). Data were analyzed using the Wilcoxon rank-sum test with adjustment for multiple comparisons (α = 0.05). As compared with the other GICs ChemFil Rock exhibited a greater increase in surface roughness (P 0.05). ChemFil Rock had significantly lower fracture toughness as compared with EQUIA Fil (P = 0.01) and significantly higher fracture toughness as compared with the other GICs (P < 0.02). In conclusion, as compared with the three other commercially available GICs, ChemFil Rock had intermediate fracture toughness, the lowest microhardness, and the greatest change in surface roughness

    The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics

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    Analysis of trends in health data collected over time can be affected by instantaneous changes in coding that cause sudden increases/decreases, or “jumps,” in data. Despite these sudden changes, the underlying continuous trends can present valuable information related to the changing risk profile of the population, the introduction of screening, new diagnostic technologies, or other causes. The joinpoint model is a well-established methodology for modeling trends over time using connected linear segments, usually on a logarithmic scale. Joinpoint models that ignore data jumps due to coding changes may produce biased estimates of trends. In this article, we introduce methods to incorporate a sudden discontinuous jump in an otherwise continuous joinpoint model. The size of the jump is either estimated directly (the Joinpoint-Jump model) or estimated using supplementary data (the Joinpoint-Comparability Ratio model). Examples using ICD-9/ICD-10 cause of death coding changes, and coding changes in the staging of cancer illustrate the use of these models

    The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics

    Get PDF
    Analysis of trends in health data collected over time can be affected by instantaneous changes in coding that cause sudden increases/decreases, or “jumps,” in data. Despite these sudden changes, the underlying continuous trends can present valuable information related to the changing risk profile of the population, the introduction of screening, new diagnostic technologies, or other causes. The joinpoint model is a well-established methodology for modeling trends over time using connected linear segments, usually on a logarithmic scale. Joinpoint models that ignore data jumps due to coding changes may produce biased estimates of trends. In this article, we introduce methods to incorporate a sudden discontinuous jump in an otherwise continuous joinpoint model. The size of the jump is either estimated directly (the Joinpoint-Jump model) or estimated using supplementary data (the Joinpoint-Comparability Ratio model). Examples using ICD-9/ICD-10 cause of death coding changes, and coding changes in the staging of cancer illustrate the use of these models

    Rydberg-atom trajectories in a ponderomotive optical lattice

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    Using semiclassical simulations, we investigate the trajectories and the microwave spectra of Rydberg atoms excited in a ponderomotive optical lattice. We relate distinct features found in the microwave spectra to characteristic types of trajectory. Several methods are presented that are designed to greatly improve the trapping efficiency of the lattice and to generalize the trapping from one to three dimensions.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85435/1/njp10_11_113036.pd
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