This study is part of the Building American Ventilation and Indoor Air Quality (BAVIAQ) field study. This study examines whole-house mechanical ventilation (WHMV) and indoor air quality (IAQ) in 51 single-family homes constructed since 2013 in the humid southeastern U.S in Florida, South Carolina, and Georgia. A total of 67 weeks of data were collected from homes monitored over one or two weeks, with whole-house mechanical ventilation (WHMV) systems either operated or not. Eleven homes were monitored under both WHMV conditions. The dataset includes time-resolved measurements of CO₂, PM2.5, formaldehyde, and radon; and time-integrated measurements of gravimetric PM2.5, NO₂, NOₓ, and formaldehyde. Occupants’ activities, including ventilation equipment usage, cooking, window opening, and other usage related to IAQ, were also monitored. Participants were asked to provide the household characteristics, their practices related to ventilation and pollutant sources and controls, and their satisfaction with air quality, thermal comfort, and other environmental factors in the home. Building envelope and duct leakage, and mechanical ventilation airflows were measured. WHMV system type, control, labeling, operational status, and ASHRAE 62.2–2010 compliance were documented. The dataset supports research on IAQ impacts of WHMV systems, building performance gaps, occupant behavior, and pollutant exposure in energy-efficient residential buildings. It enables paired comparisons under controlled conditions and provides a foundation for evaluating compliance with ventilation standards and their effects on indoor pollutant levels.

The western honey bee, Apis mellifera, continues to experience widespread die-offs that threaten their critical ecological and agricultural roles. Given the recognized impact of viruses on the increased mortality rates, it is imperative to understand the forces shaping viral infections. In this study, we explore how hive husbandry, landscape, and immunity influence viral loads in managed bees. We characterized 43 apiaries across Central Florida for eight husbandry interventions, five landscape variables, transcription of four immune genes, and infection intensities of four viruses: Black Queen Cell Virus (BQCV), Deformed Wing Virus (DWV-A), Lake Sinai Virus (LSV-2), and Israeli Acute Paralysis Virus (IAPV). We found that colonies surrounded by more floral resources and fresh water bodies were associated with increased viral loads and increased viral coinfections. We speculate that increased floral resources increased pollinator abundance, thereby increasing transmission rates and viral richness. We further speculate that increased open water similarly increased pollinator abundance and/or exposure to immunity-altering pesticides. Last, we show that husbandry interventions aimed at reducing Varroa destructor mites can have positive and negative off-target viral impacts. Our data underscore the importance of landscape, immunity, and husbandry in honey bee disease dynamics and highlight the complexity of their interactions.

This dataset contains the OSA measurements underlying “Resonance-free Fabry–Pérot cavity via unrestricted orbital-angular-momentum ladder-up” paper. We provide transmitted spectra from (i) a conventional resonant Fabry–Pérot cavity and (ii) the resonance-free Fabry–Pérot cavity (RFC). Spectra were acquired by coupling the cavity output into a multimode fiber connected to a Yokogawa AQ6370 OSA (≈0.02 nm resolution) Files include the total output spectra for FP and RFC at each cavity lenth (L), L=1.3, 1.8, 2.3, .... 4.8 mm;the input-source spectrum at different output powers of 30,40, 50 watts (for reference);and the per-mode spectra for LG1, LG3, and LG5 (for L=1.3 mm) also uploaded.

This dataset contains the OSA measurements underlying “Resonance-free Fabry–Pérot cavity via unrestricted orbital-angular-momentum ladder-up” paper. We provide transmitted spectra from (i) a conventional resonant Fabry–Pérot cavity and (ii) the resonance-free Fabry–Pérot cavity (RFC). Spectra were acquired by coupling the cavity output into a multimode fiber connected to a Yokogawa AQ6370 OSA (≈0.02 nm resolution) Files include the total output spectra for FP and RFC at each cavity lenth (L), L=1.3, 1.8, 2.3, .... 4.8 mm;the input-source spectrum at different output powers of 30,40, 50 watts (for reference);and the per-mode spectra for LG1, LG3, and LG5 (for L=1.3 mm) also uploaded.

Determining the habitability of terrestrial exoplanets is a complex problem that represents the next major step for the astrophysical community. The majority of current models treat these planets as homogeneous or contain heterogeneity that is constant in time. In reality, habitable exoplanets are expected to contain atmospheric and surface heterogeneities similar to Earth, with diurnal rotation, seasonal changes, and weather patterns resulting in complex, time-dependent signatures. Due to its ability to measure light as a vector, polarimetry provides an important tool that will enhance the characterizations of heterogeneous worlds. Here we model the visible to near-infrared linear spectropolarimetric signatures, as functions of wavelength and planetary phase angle, of various heterogeneous Earth scenarios as well as the first signals of an early wet and potentially habitable Mars. The contributions from the different atmospheric and surface properties result in asymmetric phase curves and variable spectra, with the polarization appearing to be more sensitive than flux to heterogeneities such as patchy clouds and continents moving into and out-of-view. Our models provide important predictions of expected polarized and unpolarized signatures of heterogeneous exoplanets that will help guide the designs and observing plans of future polarimeters, including those proposed for the upcoming Habitable Worlds Observatory.This dataset contains all modeled spectropolarimetric signatures used to conduct this work. Each .zip file contains the output folders for one of the four main categories of models from our study: Sandy Continent, Snowball Earth, Modern Earth, and Early Mars. Each of these top-level folders then contains individual sub-folders for each specific model run. The names for each of these individual sub-folders describes the specific model. Finally, each individual sub-folder then contains files for the spectropolarimetric signatures, where each file contains five columns of data representing the spectra for that specific model at that specific planetary phase angle. Please refer to the README.txt as well as the accompanying manuscript for more information.

Determining the habitability of terrestrial exoplanets is a complex problem that represents the next major step for the astrophysical community. The majority of current models treat these planets as homogeneous or contain heterogeneity that is constant in time. In reality, habitable exoplanets are expected to contain atmospheric and surface heterogeneities similar to Earth, with diurnal rotation, seasonal changes, and weather patterns resulting in complex, time-dependent signatures. Due to its ability to measure light as a vector, polarimetry provides an important tool that will enhance the characterizations of heterogeneous worlds. Here we model the visible to near-infrared linear spectropolarimetric signatures, as functions of wavelength and planetary phase angle, of various heterogeneous Earth scenarios as well as the first signals of an early wet and potentially habitable Mars. The contributions from the different atmospheric and surface properties result in asymmetric phase curves and variable spectra, with the polarization appearing to be more sensitive than flux to heterogeneities such as patchy clouds and continents moving into and out-of-view. Our models provide important predictions of expected polarized and unpolarized signatures of heterogeneous exoplanets that will help guide the designs and observing plans of future polarimeters, including those proposed for the upcoming Habitable Worlds Observatory.This dataset contains all modeled spectropolarimetric signatures used to conduct this work. Each .zip file contains the output folders for one of the four main categories of models from our study: Sandy Continent, Snowball Earth, Modern Earth, and Early Mars. Each of these top-level folders then contains individual sub-folders for each specific model run. The names for each of these individual sub-folders describes the specific model. Finally, each individual sub-folder then contains files for the spectropolarimetric signatures, where each file contains five columns of data representing the spectra for that specific model at that specific planetary phase angle. Please refer to the README.txt as well as the accompanying manuscript for more information.

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Overwintering populations of the monarch butterfly, Danaus plexippus, have been in decline for the past 30 years. Several hypotheses for the decline have been proposed including summer and winter habitat loss and migration mortality due to non-senescing milkweeds and the parasite Ophryocystis elektroscirrha (OE). How climate change will affect migration physiology, however, has been understudied. This is surprising because warmer temperatures will likely destabilize reproductive diapause, a physiological strategy central to migration and overwintering success. Here, we exposed wild-caught migrating monarchs to different field-realistic migratory temperatures under laboratory conditions for 30 days, followed by different overwintering temperatures until death. During the migratory phase, warmer temperatures reduced male body condition, increased male mortality, increased mating frequency, and caused females to prematurely abandon diapause and invest in oocytes in the absence of milkweed. Monarchs who experienced warm migratory conditions prior to overwintering also exhibited greater overwintering reproductive investment and mortality. Overall, reproductive investment and OE burden were the best predictors of death. These data suggest that warm migratory temperature significantly alters monarch physiology and fitness and provide a mechanism by which climate change can facilitate migratory failure, winter-breeding, and overwintering mortality, all of which decrease overwintering population size.

The files listed here contain the data used for Figures 3, 4, 5, and 6 and Supplemental Figures S1b, S2, and S3 of the paper titled "The Influence of Space Weathering on the Far-Ultraviolet Reflectance of Apollo-era Soils." The experimentally derived phase curve data from Figure 3 are contained in the .txt files which have the material name (Apollo 10084, 68501, or 71061) followed by "BRDF," the wavelength in Angstroms (1216, 1400, or 1600), and "Data" in the file name.  Files with the fitted Hapke photometric model curves have "Hapke" in place of "Data" in the name.  All files with "Hapke" in the file name are the Hapke photometric model (Hapke, 2012) fitted phase curves for the associated experimental data.Figure 4 TEM images are included as .tiff files, with the sample indicated followed by which image pane the image belongs to ("FullGrain" for the first wide field image in line, 1, 2, or 3).  The Apollo 71061 images also include "G1" or "G2" for the two different grains presented.  Particle size distribution data as presented in Figure 4 is contained in the .txt files with "Fig4" in the file name.The nested sampling results used in Figure 5 are in the .csv file with "Fig5" in the name, with the supplementary examples for Apollo 68501 and 71061 similarly identified with "FigS3a" and "FigS3b," respectively.Figure 6 contains datapoints already listed in supplemental tables S1, S2, and S3.  The Hapke "hockeystick" curve data plotted in Figure 6D is included in this dataset as Fig6d_HapkeHockeystickCurve.txt.Elemental maps presented in Figure S1b are included as .tiffs with the sample name and the element mapped indicated in the file name.  X-ray counts associated with these maps are included in .txt files with "FigS1b" and the sample name in the title.The supplemental images in Figure S2 are included as .tiffs with the sample name, "SEM," and "W" or "N" for the wide angle and zoomed fields, respectively.