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Abstract Scanning Ka-band Doppler radar observations reveal the development and intensification of a counter-rotating vortex pair (CVP) embedded in an advancing fire front during California’s Dixie Fire in August 2021. The observations show that an initially isolated plume associated with a new spot fire develops flow splitting and a fire-generated inflow wind on the plume’s lee side. This inflow retards the fire progression and enhances the lateral wind shear along the plume flanks. The lateral shear evolves into quasi-symmetric cyclonic and anticyclonic vortices with winds > 40 m s⁻¹. This CVP spreads perpendicular to the wind direction, yielding a “y-shaped” fire perimeter, with fire intensity and direction of spread strongly linked to the vortices. Detailed snapshots of the vortices reveal associated radar “hook echoes” and orbiting subvortices of tornado-like intensity. Some vortices remain attached to the fire, while others shed downstream. Additional lidar observations show the structure and development of the fire’s inflow. We discuss the observed vortex evolution in the context of existing conceptualizations for CVPs in wildland fire, including their preferential occurrence on lee slopes and their role in generating lateral fire spread. 

Welcome to this special edition of our journal. This issue brings together the historical accounts of fifteen major museum based molluscan collections in the U.S., in addition to an introductory article prepared by curators, collection managers, and collection associates involved in the project. Throughout its 139-year existence, The Nautilus has endeavored to promote collection-based malacological research, so it is only natural that the journal would be the vehicle to disseminate this “historical” compilation. The articles are an outcome of the National Science Foundation-sponsored Thematic Collections Network (TCN) grants collectively known as Mobilizing Millions of Mollusks of the Eastern Seaboard (ESB). Each tells the story of an institutional mollusk collection from its earliest days to its present involvement in community-wide efforts. The introductory article reflects on the changing roles of U.S. malacological collections in a digital world, summarizes common needs and concerns, and points to the uniqueness and innovative nature of the ESB project. The editors want to acknowledge the indispensable assistance of the following peer reviewers, many of whom reviewed more than one manuscript in the course of this work: Arthur E. Bogan, Christopher Boyko, Eugene V. Coan, Kevin Cummings, Emilio F. García, Daniel Graf, Lindsey Groves, M. G. Harasewych, Alan Kabat, Rafael Lemaitre, Charles Lydeard, Paula M. Mikkelsen, Aydin Örstan, Shirley Pomponi, Carrie Schweitzer, Elizabeth K. Shea, Leslie Skibinski, John Slapcinsky, Ángel Valdés, and some others who preferred to remain anonymous. This assemblage of historical accounts could only come to fruition thanks to the cooperative and collegial environment of the ESB consortium; we hope that you find as much enjoyment reading these narratives as we did organizing and editing them. Support for this publication under National Science Foundation award DBI-2001510 is gratefully acknowledged. 

Abstract Real‐life data often include both numerical and categorical features. When categorical features are ordinal, the Pearson correlation matrix (CM) can be extended to a heterogeneous CM (HCM), which combines Pearson's correlations (numerical‐numerical), polyserial correlations (numerical‐ordinal) and polychoric correlations (ordinal‐ordinal). HCM entries are comparable, enabling assessment of pairwise‐linear dependencies. An added benefit is the computation of ‐values for pairwise uncorrelation tests, forming a heterogeneous ‐values matrix (HPM). While the HCM has been used for unsupervised feature extraction (UFE), that is, transforming features into informative representations (e.g., PCA), its application to unsupervised feature selection (UFS), that is, selecting relevant features, remains unexplored. This paper proposes two HCM‐based UFS methods for mixed‐type features. These, called UFS‐rHCM and UFS‐cHCM, iteratively remove redundant features using the HCM—row‐wise (UFS‐rHCM) or cell‐wise (UFS‐cHCM). The HPM determines the stopping point, enabling a statistically grounded approach to selecting the number of features. We also introduce a visualization tool for assessing feature importance and ranking. The performance of our methods is evaluated on simulated and real datasets. 

Abstract Nest-site choice influences offspring development and varies in response to specific environmental cues. For species that inhabit coastal regions, salinity of the nest site is probably an important factor for nesting females, whereas this cue is likely to be rare or absent for inland populations. We compared nest-site choice of brown anole lizards (Anolis sagrei) between an island population (that frequently experiences seawater inundation) and an inland population (that rarely, if ever, experiences inundation). We hypothesized that island females would avoid nesting in saline soils more than inland females, because it impairs egg hatching success. We provided females from each population with two different nesting substrates (soil mixed with freshwater vs. saltwater). We incubated their eggs in these conditions to quantify the effects on embryo survival. Island females tended to avoid nesting in saltwater soil, whereas inland females exhibited no preference. Water loss and mortality rates of eggs increased during incubation in soil with saltwater. These patterns imply that females from island populations, but not inland populations, might have adaptive behavioural responses to soil salinity. These results have important implications for understanding how coastal or island populations might respond to changes in salinity under climate change (e.g. sea level rise, increased hurricanes). 

Drought is a significant environmental stressor that severely impairs plant growth and agricultural productivity. Unraveling the molecular mechanisms underlying plant responses to drought is crucial for developing crops with enhanced resilience. In this study, we investigated the transcriptomic responses of cultivated tomato (Solanum lycopersicum) and its drought-tolerant wild relative,Solanum pennellii, to identify “stress-ready” gene expression patterns associated with pre-adaptation to arid environments. Through RNA-seq analysis, we identified orthologous genes between the two species and compared their transcriptomic profiles under both control and drought conditions. Approximately 43% of the orthologous genes exhibited species-specific expression patterns, while nearly 20% were classified as stress-ready. These stress-ready genes were significantly enriched for functions related to nucleosome assembly, RNA metabolism, and transcriptional regulation. Furthermore, transcription factor binding motif analysis revealed a marked enrichment of ERF family motifs, emphasizing their role in both stress-ready and species-specific responses. Our findings indicate that regulatory mechanisms, particularly those mediated by ERF transcription factors, are pivotal to the drought resilience ofS. pennellii, providing a foundation for future crop improvement strategies. 

Abstract A major goal of cosmology is to understand the nature of the field(s) which drove primordial Inflation. Through future observations, the statistics of large-scale structure will allow us to probe primordial non-Gaussianity of thecurvature perturbation at the end of Inflation. We show how a new correlation statistic can significantly improve these constraints over conventional methods. Next-generation radio telescope arrays are under construction which will map the density field of neutral hydrogen to high redshifts. These telescopes can operate as an interferometer, able to probe small scales, or as a collection of single dishes, combining signals to map the large scales. We show how to fuse these operating modes in order to measure the squeezed bispectrum with higher precision and greater economy. This leads to constraints on primordial non-Gaussianity that will improve on measurements by Planck,and out-perform other surveys such as Euclid. We forecast that σ(f_NL^loc)∼ 3, achieved by using a small subset, 𝒪(10²- 10³), of the total number of accessible triangles. The proposed method identifies a low instrumental noise, systematic-free scale regime, enabling clean squeezed bispectrum measurements. This provides a pristine window into local primordial non-Gaussianity, allowing tight constraints not only on primordial non-Gaussianity, but on any observable that peaks in squeezed configurations.