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This dataset includes anonymized survey data collected in communities affected by the East Palestine train derailment, chemical spill, and fires. The survey was designed to capture community perceptions and experiences related to air, water, and soil sampling and testing; household and built environment impacts; and protective actions taken. Participants were eligible to participate if they were 18 years or older and lived or worked in an affected county as of February 3, 2023—the day of the derailment. The survey was open from July 20 to September 20, 2023, approximately six months after the incident. See "Notes" below for more details on the methods. The research was reviewed and approved by the Human Subjects in Research Ethics boards at the authors’ universities. This research is supported by the National Science Foundation (Award #2329409). 

Data on five Washington Double Star catalog binaries were collected from the Dimension Point Observatory (Mayhill, New Mexico) and Las Cumbres Observatory (Cerro Tololo, Chile) on February 19, 2025, and March 5, 2025, respectively. Student researchers participating in the Four Corners Research Seminar measured the position angle (θ/deg) and Separation (ρ/arcsec) of each target using AstroImageJ and an author-created script utilizing the Astropy module in Python3. Each target was imaged using a variety of instruments, filters, and exposure times. Compared to the extrapolated 6th Orbit Catalog estimates, measurements using AstroImageJ were within 1.52% of θ and 14.87% of ρ, while the author’s automated code method provided measurements within 4.09% of θ and 16.59% of ρ. 

University students have begun to use Artificial Intelligence (AI) in many different ways in their undergraduate education, some beneficial to their learning, and some simply expedient to completing assignments with as little work as possible. This exploratory qualitative study examines how undergraduate students used AI in a large General Education course on sustainability and technology at a research university in the United States in 2023. Thirty-nine students documented their use of AI in their final course project, which involved analyzing conceptual networks connecting core sustainability concepts. Through iterative qualitative coding, we identified key patterns in students’ AI use, including higher-order writing tasks (understanding complex topics, finding evidence), lower-order writing tasks (revising, editing, proofreading), and other learning activities (efficiency enhancement, independent research). Students primarily used AI to improve communication of their original ideas, though some leveraged it for more complex tasks like finding evidence and developing arguments. Many students expressed skepticism about AI-generated content and emphasized maintaining their intellectual independence. While some viewed AI as vital for improving their work, others explicitly distinguished between AI-assisted editing and their original thinking. This analysis provides insight into how students navigate AI use when it is explicitly permitted in coursework, with implications for effectively integrating AI into higher education to support student learning. 

The 6 February 2023 Türkiye earthquakes and the accompanying aftershocks were a once-in-a-century catastrophe that has greatly impacted Türkiye and Syria. The repercussions of these events will have a lasting effect on the entire region. This article documents the geotechnical and geological observations performed by GEER (Geotechnical Extreme Events Reconnaissance) immediately following the events. Observations of ground damage, including surface fault rupture, liquefaction and lateral spreading, landslides and rock falls, and foundation failure of buildings, dams, and other civil infrastructure, are described herein. This article summarizes the key findings that were originally reported in the joint GEER-EERI (Earthquake Engineering Research Institute) reconnaissance report. The goal of these reconnaissance efforts is to document perishable data and disseminate it widely so that lessons can be learned from these events. 

An internal tide model, ZHAO30yr, is developed using 30 years of satellite altimetry sea surface height (SSH) measurements from 1993 to 2022 by a recently improved mapping technique that consists of two rounds of plane wave analysis with a spatial bandpass filter in between. Prerequisite wavelengths are calculated using climatological annual mean hydrographic profiles in the World Ocean Atlas 2018. ZHAO30yr only extracts the 30-year phase-locked internal tide component, lacking the incoherent component caused by the time-varying ocean environment. The model contains 12 internal tide constituents: eight mode-1 constituents (M2, S2, N2, K2, K1, O1, P1, and Q1) and four mode-2 constituents (M2, S2, K1, and O1). Model errors are estimated to be lower than 1 mm in the SSH amplitude on global average, thanks to the long data record and improved mapping technique. The model is evaluated by making internal tide correction to independent altimetry data for 2023. A total of 10 constituents (but for K2 and Q1) can reduce variance on global average. K2 and Q1 can only cause variance reductions in their source regions. The model decomposes the multiconstituent, multimodal, multidirectional internal tide field into a series of simple plane waves at each grid point. The decomposition reveals unprecedented features previously masked by multiwave interference. The model divides each internal tide constituent into components by propagation direction. The directionally decomposed components show numerous long-range internal tidal beams associated with notable topographic features. The semidiurnal internal tidal beams off the Amazon shelf and the diurnal internal tidal beams in the Arabian Sea are examined in detail. ZHAO30yr is available at https://doi.org/10.6084/m9.figshare.28078523 (Zhao, 2024b). Model errors are available at https://doi.org/10.6084/m9.figshare.28559978.v3 (Zhao, 2025). 

ABSTRACT The February 2023 Türkiye–Syria Earthquake had a profound impact on political, economic, and social life in Türkiye. Despite criticism about government disaster response, the government of Türkiye won an election 3 months later. We examine variance in media coverage of government disaster responses with Structural Topic Modeling of 12,268 articles in five pro‐ and anti‐government newspapers in Türkiye (Anadolu Ajansi, Hurriyet, Sozcu, Cumhuriyet, and Posta) between the February earthquake and the May election. We identify five general topical themes in the data: emotion, science, information provision, government response, and the economy. We conduct sentiment analysis and find little direct criticism of the government's responses, although anti‐government newspapers are more negative on topics related to building structures and damage. The general pattern of positive sentiment among all newspapers regarding government responses to the earthquake may help us understand why the disaster was not as consequential for the election outcome as some observers expected. 

Abstract The Winter Precipitation Type Research Multiscale Experiment (WINTRE-MIX) was conducted during February–March 2022 to observe multiscale processes impacting the variability and predictability of precipitation type and amount under near-freezing conditions over the Saint Lawrence River valley. Intensive observation period (IOP) 4 of the campaign occurred 17–18 February 2022 in association with an upper-level trough positioned over the north-central United States and a surface cyclone that traversed the study domain along a frontal boundary that extended northeast of the cyclone. The timing of precipitation-type transitions during the event was consistently too slow within operational forecast models at 2–5-day lead times. Consequently, this study aims to understand how forecast model representations of dynamical and thermodynamical processes on the synoptic scale to mesoscale may have influenced the predictability of precipitation type during IOP4. To do so, an ensemble of operational forecasts from the Global Ensemble Forecast System initialized 5 days prior to IOP4 was divided into three clusters according to the strength and position of the frontal zone over the Saint Lawrence River Valley during the event. Ensemble sensitivity analyses and spatial composites suggest that differences in the position of the frontal zone between clusters are dynamically linked to the differences in the structure of the associated upstream upper-level trough at prior forecast lead times. A diagnosis of the divergent circulation prior to the event suggests that feedback mechanisms between the surface cyclone, its attendant frontal boundaries, and the upper-level flow pattern help to further explain differences in the frontal zone between clusters. Significance StatementMixed-phase precipitation events, which can produce rain, freezing rain, ice pellets, and snow, are difficult to accurately forecast. This study investigates the large-scale processes influencing our ability to accurately forecast the precipitation type and amount during one of these events that was observed by a field campaign in February 2022. In forecasts initialized 5 days prior to the event, differences in the forecast upper-level atmospheric conditions led to differences in the forecast interactions between the upper-level flow and a low pressure system at the surface. As a result, there was large uncertainty in the predicted position of a surface front associated with the low pressure system and the precipitation-type distribution during the event. 

ABSTRACT Scientific publications, textbooks, and online educational resources rely on illustrated figures to communicate about molecular structures like genes and chromosomes. Published figures have the potential to shape how learners think about these molecular structures and their functions, so it is important that figures are clear, unambiguous, and free from misleading or incorrect information. Unfortunately, we found numerous examples of figures that contain representations of genes and chromosomes with errors that reflect common molecular biology misconceptions. We found published figures featuring Y-shaped Y chromosomes, replicated chromosomes incorrectly shown with different alleles on sister chromatids, single genes portrayed as wide bands on chromosomes, and genes consisting of only a small number of nucleotides. Drawing on our research on student thinking about visual representations in molecular biology, we critique these published figures that contain such misconceptions and provide recommendations for simple modifications to figures that may help scientists, science illustrators, and science educators more accurately communicate the structure and function of genes and chromosomes. 

Abstract The Sunspot Solar Observatory Data Archive (SSODA) stores data acquired with the suite of instruments at the Richard B. Dunn Solar Telescope (DST) from February 2018 to the present. The instrumentation at the DST continues to provide high cadence imaging, spectroscopy, and polarimetry of the solar photosphere and chromosphere across a wavelength range from 3500 Å to 11,000 Å. At the time of writing, the archive contains approximately 374 TiB of data across more than 520 observing days (starting on February 1, 2018). These numbers are approximate as the DST remains operational, and is actively adding new data to the archive. The SSODA includes both raw and calibrated data. A subset of the archive contains the results of photospheric and chromospheric spectropolarimetric inversions using the Hazel-2.0 code to obtain maps of magnetic fields, temperatures, and velocity flows. The SSODA represents a unique resource for the investigation of plasma processes throughout the solar atmosphere, the origin of space weather events, and the properties of active regions throughout the rise of Solar Cycle 25. 

For the last 10 years, our university has offered a two-semester bridge into a master's in computer science for people with undergraduate degrees in non-computing disciplines. Since its inception, the program has expanded to eight campuses across North America and has opened admission to students from all disciplines, including non-STEM disciplines. The bridge program has over 2000 currently enrolled students, with more than 50% women every year since 2020, and domestic enrollment has increased relative to direct entry master's students. Our data show that bridge students, including those with non-STEM backgrounds, perform comparably to direct entry students in terms of GPA. We attribute much of the program's success to institutional investment in resources specifically designed to meet the unique needs of bridge students. These resources include dedicated academic and career advising, co-curricular programming, and the hiring of full-time teaching faculty specifically recruited to teach these bridge students. This paper examines data pertaining to the bridge program and MSCS from 2013 to 2023; it includes analyses of the expansion of the bridge program to eight campuses in North America, the admission of students with non-STEM degrees to the bridge, the achievement of enrolling over 50% women and non-binary identifying students, the success of bridge students in the MSCS program and in obtaining job placements, and domestic student enrollment growth as compared to traditional direct entry master's students.