Many warnings issued to members of the public are deterministic in that they do not include event likelihood information. This is true of the current polygon-based tornado warning used by the American National Weather Service, although the likelihood of a tornado varies within the boundaries of the polygon. To test whether adding likelihood information benefits end users, two experimental studies and one in-person interview study were conducted. The experimental studies compared five probabilistic formats, two with color and three with numeric probabilities alone, to the deterministic polygon. In both experiments, probabilistic formats led to better understanding of tornado likelihood and higher trust than the polygon alone, although color-coding led to several misunderstandings. When the polygon boundary was drawn at 10% chance, those using probabilistic formats made fewer correct shelter decisions at low probabilities and more correct shelter decisions at high probabilities compared to those using the deterministic warning, although overall decision quality, operationalized as expected value, did not differ. However, when the polygon boundary was drawn around 30%, participants with probabilistic forecasts had higher expected value. The interview study revealed that, although tornado-experienced individuals would not shelter at 10% chance, they would take intermediate actions, such as information-seeking and sharing. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
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Sci Rep
January 2025
Medical Physics, Department of Diagnostic and Interventional Radiology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, 79106, Freiburg, Germany.
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View Article and Find Full Text PDFNeural Netw
December 2024
School of Information Science and Technology, Taishan University, Taian, 271000, Shandong, China.
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View Article and Find Full Text PDFBMC Glob Public Health
October 2024
Department of Civil and Systems Engineering, Johns Hopkins University, Baltimore, MD, USA.
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View Article and Find Full Text PDFPlant Phenomics
December 2024
Department of General and Organic Viticulture, Hochschule Geisenheim University, Geisenheim, Germany.
Understanding root system architecture (RSA) is essential for improving crop resilience to climate change, yet assessing root systems of woody perennials under field conditions remains a challenge. This study introduces a pipeline that combines field excavation, in situ 3-dimensional digitization, and transformation of RSA data into an interoperable format to analyze and model the growth and water uptake of grapevine rootstock genotypes. Eight root systems of each of 3 grapevine rootstock genotypes ("101-14", "SO4", and "Richter 110") were excavated and digitized 3 and 6 months after planting.
View Article and Find Full Text PDFDue to its large transmission capacity and low complexity, probabilistic shaping (PS) technology has been attracting increasing attention. The commonly used constant composition distribution matching (CCDM) in PS technology, which generates amplitude sequences with a fixed empirical distribution, exhibits higher rate loss for short block lengths. In this paper, we present a block-length aware enumerative sphere shaping (BA-ESS) designed to implement probability shaping within high-order modulation formats, which can transition between static (BA-ESS-S) and dynamic (BA-ESS-D) modes based on the block length.
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