Rutgers University

About: Rutgers University is a education organization based out in New Brunswick, New Jersey, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 68736 authors who have published 159418 publications receiving 6713860 citations. The organization is also known as: Rutgers, The State University of New Jersey & Rutgers.

The precaution adoption process.

Abstract: This article presents a critique of current models of preventive behavior. It discusses a variety of factors that are usually overlooked-including the appearance of costs and benefits over time, the role of cues to action, the problem of competing life demands, and the ways that actual decision behavior differs from the rational ideal implicit in expectancy-value and utility theories. Such considerations suggest that the adoption of new precautions should be viewed as a dynamic process with many determinants. The framework of a model that is able to accommodate these additional factors is described. This alternative model portrays the precaution adoption process as an orderly sequence of qualitatively different cognitive stages. Data illustrating a few of the suggestions made in the article are presented, and implications for prevention programs are discussed.

A Level Set Method for Image Segmentation in the Presence of Intensity Inhomogeneities With Application to MRI

Abstract: Intensity inhomogeneity often occurs in real-world images, which presents a considerable challenge in image segmentation. The most widely used image segmentation algorithms are region-based and typically rely on the homogeneity of the image intensities in the regions of interest, which often fail to provide accurate segmentation results due to the intensity inhomogeneity. This paper proposes a novel region-based method for image segmentation, which is able to deal with intensity inhomogeneities in the segmentation. First, based on the model of images with intensity inhomogeneities, we derive a local intensity clustering property of the image intensities, and define a local clustering criterion function for the image intensities in a neighborhood of each point. This local clustering criterion function is then integrated with respect to the neighborhood center to give a global criterion of image segmentation. In a level set formulation, this criterion defines an energy in terms of the level set functions that represent a partition of the image domain and a bias field that accounts for the intensity inhomogeneity of the image. Therefore, by minimizing this energy, our method is able to simultaneously segment the image and estimate the bias field, and the estimated bias field can be used for intensity inhomogeneity correction (or bias correction). Our method has been validated on synthetic images and real images of various modalities, with desirable performance in the presence of intensity inhomogeneities. Experiments show that our method is more robust to initialization, faster and more accurate than the well-known piecewise smooth model. As an application, our method has been used for segmentation and bias correction of magnetic resonance (MR) images with promising results.

Recent Arctic amplification and extreme mid-latitude weather

Abstract: The Arctic region has warmed more than twice as fast as the global average — a phenomenon known as Arctic amplification. The rapid Arctic warming has contributed to dramatic melting of Arctic sea ice and spring snow cover, at a pace greater than that simulated by climate models. These profound changes to the Arctic system have coincided with a period of ostensibly more frequent extreme weather events across the Northern Hemisphere mid-latitudes, including severe winters. The possibility of a link between Arctic change and mid-latitude weather has spurred research activities that reveal three potential dynamical pathways linking Arctic amplification to mid-latitude weather: changes in storm tracks, the jet stream, and planetary waves and their associated energy propagation. Through changes in these key atmospheric features, it is possible, in principle, for sea ice and snow cover to jointly influence mid-latitude weather. However, because of incomplete knowledge of how high-latitude climate change influences these phenomena, combined with sparse and short data records, and imperfect models, large uncer - tainties regarding the magnitude of such an influence remain. We conclude that improved process understanding, sustained and additional Arctic observations, and better coordinated modelling studies will be needed to advance our understanding of the influences on mid-latitude weather and extreme events.

Epistemologically Authentic Inquiry in Schools: A Theoretical Framework for Evaluating Inquiry Tasks

Abstract: A main goal of science education is to help students learn to reason scien- tifically. A main way to facilitate learning is to engage students in inquiry activities such as conducting experiments. This article presents a theoretical framework for evaluating inquiry tasks in terms of how similar they are to authentic science. The framework helps identify the respects in which these reasoning tasks are similar to and different from real scientific research. The framework is based on a recent theory of reasoning, models-of-data theory. We argue that inquiry tasks commonly used in schools evoke reasoning processes that are qualitatively different from the processes employed in real scientific inquiry. More- over, school reasoning tasks appear to be based on an epistemology that differs from the epistemology of authentic science. Inquiry tasks developed by researchers have increas- ingly captured features of authentic science, but further improvement is still possible. We conclude with a discussion of the implications of our analysis for research, assessment, and instruction. C