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In this study, a detailed metric survey on the “Galaxy 15” (April 2010) space weather event is conducted to validate MAGNetosphere–Ionosphere–Thermosphere (MAGNIT), a semi-physical auroral ionospheric conductance model characterizing four precipitation sources, against AMPERE measurements via field-aligned current (FAC) characteristics. As part of this study, the comparative performance of three ionosphere electrodynamic specifications involving auroral conductance models, MAGNIT, Ridley Legacy Model (RLM) (empirical), and Conductance Model for Extreme Events (CMEE) (empirical), within the Space Weather Modeling Framework (SWMF), is demonstrated. Overall, MAGNIT exhibits marginally improved predictions; root mean square error values in upward and downward FACs of MAGNIT predictions compared to AMPERE data are smaller than those of CMEE and Ridley Ionosphere Model (RIM) by $\sim$12.7% and $\sim$6.24% before the storm, $\sim$4.52% and $\sim$2.13% better during the main phase, $\sim$1.98% and $\sim$1.27% worse during the second minimum, and better by $\sim$1.84% and $\sim$1.49% by the beginning of the recovery, respectively. In all three model configurations, the dusk and night magnetic local time (MLT) sectors over-predict throughout the storm, while the day and dawn MLT sectors under-predict in response to interplanetary magnetic field (IMF) conditions. In addition to accuracy and bias, similar results and conclusions are drawn from additional metrics, including in the categories of correlation, precision, extremes, and skill, and recommendations are made for the best-performing model configuration in each metric category. Visual data–model comparisons conducted by studying the FAC location and latitude/MLT spread throughout various phases of the storm suggest that the spatial extent of the FACs is captured relatively well in the night-side auroral oval, unlike in the day-side oval. The spread in latitude of the FACs matches that in the previous literature on other model performances. This information on auroral precipitation sources and their weight on FACs, along with metrics from model–data comparisons, can be used to modify MAGNIT settings to optimize SWMF model performance. 

Habituation to signals that warn of a potential danger in high-risk work environments is a critical causal factor of workplace accidents. Such habituation is hard to measure in a real-world setting, and no existing intervention can effectively curb it. Here, we present a protocol to enhance workers’ sensory responses to frequently encountered warnings at workplaces using a virtual-reality-based behavioral intervention. We describe steps for performing a virtual reality experiment and an electroencephalography (EEG) experiment with human participants. 

Abstract Neuromorphic computing shows promise for advancing computing efficiency and capabilities of AI applications using brain-inspired principles. However, the neuromorphic research field currently lacks standardized benchmarks, making it difficult to accurately measure technological advancements, compare performance with conventional methods, and identify promising future research directions. This article presents NeuroBench, a benchmark framework for neuromorphic algorithms and systems, which is collaboratively designed from an open community of researchers across industry and academia. NeuroBench introduces a common set of tools and systematic methodology for inclusive benchmark measurement, delivering an objective reference framework for quantifying neuromorphic approaches in both hardware-independent and hardware-dependent settings. For latest project updates, visit the project website (neurobench.ai). 

Abstract Hypothesis-driven research rests on clearly articulated scientific theories. The building blocks for communicating these theories are scientific terms. Obviously, communication – and thus, scientific progress – is hampered if the meaning of these terms varies idiosyncratically across (sub)fields and even across individual researchers within the same subfield. We have formed an international group of experts representing various theoretical stances with the goal to homogenize the use of the terms that are most relevant to fundamental research onvisual distractionin visual search. Our discussions revealed striking heterogeneity and we had to invest much time and effort to increase our mutual understanding of each other’s use of central terms, which turned out to be strongly related to our respective theoretical positions. We present the outcomes of these discussions in a glossary and provide some context in several essays. Specifically, we explicate how central terms are used in the distraction literature and consensually sharpen their definitions in order to enable communication across theoretical standpoints. Where applicable, we also explain how the respective constructs can be measured. We believe that this novel type of adversarial collaboration can serve as a model for other fields of psychological research that strive to build a solid groundwork for theorizing and communicating by establishing a common language. For the field of visual distraction, the present paper should facilitate communication across theoretical standpoints and may serve as an introduction and reference text for newcomers. 

During geomagnetic storms a large amount of energy is transferred into the ionosphere-thermosphere (IT) system, leading to local and global changes in e.g., the dynamics, composition, and neutral density. The more steady energy from the lower atmosphere into the IT system is in general much smaller than the energy input from the magnetosphere, especially during geomagnetic storms, and therefore details of the lower atmosphere forcing are often neglected in storm time simulations. In this study we compare the neutral density observed by Swarm-C during the moderate geomagnetic storm of 31 January to 3 February 2016 with the Thermosphere-Ionosphere-Electrodynamics-GCM (TIEGCM) finding that the model can capture the observed large scale neutral density variations better in the southern than northern hemisphere. The importance of more realistic lower atmospheric (LB) variations as specified by the Whole Atmosphere Community Climate Model eXtended (WACCM-X) with specified dynamics (SD) is demonstrated by improving especially the northern hemisphere neutral density by up to 15% compared to using climatological LB forcing. Further analysis highlights the importance of the background atmospheric condition in facilitating hemispheric different neutral density changes in response to the LB perturbations. In comparison, employing observationally based field-aligned current (FAC) versus using an empirical model to describe magnetosphere-ionosphere (MI) coupling leads to an 7–20% improved northern hemisphere neutral density. The results highlight the importance of the lower atmospheric variations and high latitude forcing in simulating the absolute large scale neutral density especially the hemispheric differences. However, focusing on the storm time variation with respect to the quiescent time, the lower atmospheric influence is reduced to 1–1.5% improvement with respect to the total observed neutral density. The results provide some guidance on the importance of more realistic upper boundary forcing and lower atmospheric variations when modeling large scale, absolute and relative neutral density variations.