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The eight-planet Kepler-90 system exhibits the greatest multiplicity of planets found to date. All eight planets are transiting and were discovered in photometry from the NASA Kepler primary mission. The two outermost planets, g (Pg = 211 days) and h (Ph = 332 days), exhibit significant transit-timing variations (TTVs), but were only observed six and three times, respectively, by Kepler. These TTVs allow for the determination of planetary masses through dynamical modeling of the pair’s gravitational interactions, but the paucity of transits allows a broad range of solutions for the masses and orbital ephemerides. To determine accurate masses and orbital parameters for planets g and h, we combined 34 radial velocities (RVs) of Kepler-90, collected over a decade, with the Kepler transit data. We jointly modeled the transit times of the outer two planets and the RV time series, then used our two-planet model to predict their future times of transit. These predictions led us to recover a transit of Kepler-90 g with ground-based observatories in 2024 May. We then combined the 2024 transit and several previously unpublished transit times of planets g and h with the Kepler photometry and RV data to update the masses and linear ephemerides of the planets, finding masses for g and h of 15.0 ± 1.3 M⊕ and 203 ± 16 M⊕, respectively, from a Markov Chain Monte Carlo analysis. These results enable further insights into the architecturally rich Kepler-90 system and pave the way for atmospheric characterization with space-based facilities.

Scientific Community Laboratories, developed by The University of Maryland, have shown initial promise as laboratories meant to emulate the practice of doing physics. These laboratories have been re-created by incorporating their design elements with the University of Toledo course structure and resources. The laboratories have been titled the Scientific Learning Community (SLC) Laboratories. A comparative study between these SLC laboratories and the University of Toledo physics department's traditional laboratories was executed during the fall 2012 semester on first semester calculus-based physics students. Three tests were executed as pre-test and post-tests to capture the change in students' concept knowledge, attitudes, and understanding of uncertainty. The Force Concept Inventory (FCI) was used to evaluate students' conceptual changes through the semester and average normalized gains were compared between both traditional and SLC laboratories. The Colorado Learning Attitudes about Science Survey for Experimental Physics (E-CLASS) was conducted to elucidate students' change in attitudes through the course of each laboratory. Finally, interviews regarding data analysis and uncertainty were transcribed and coded to track changes in the way students understand uncertainty and data analysis in experimental physics after their participation in both laboratory type. Students in the SLC laboratories showed a notable an increase conceptual knowledge and attitudes when compared to traditional laboratories. SLC students' understanding of uncertainty showed most improvement, diverging completely from students in the traditional laboratories, who declined throughout the semester.

Many teachers and students have experienced the classic pet rock experiment in conjunction with a geology unit. A teacher has students bring in a \"pet\" rock found outside of school, and the students run geologic tests on the rock. The tests include determining relative hardness using Mohs scale, checking for magnetization, and assessing luster. While this type of lesson is concise and direct, the authors have found a new way of targeting the same Earth science benchmarks for upper elementary students. Their inquiry-based approach allows students to discover geologic properties as they befriend their pet rocks. (Contains 2 figures and 3 online resources.)

Most known planets are found around metal-rich host stars, which has made it difficult to determine whether a lower metallicity limit for planet formation exists and how the properties of planets born in low-metallicity environments may differ from those with metal-rich origins. We present the discovery and characterization of TOI-7169 b (TIC 372048733 b), a hot Jupiter that is orbiting a spectroscopically-confirmed metal-poor ([Fe/H] = -0.72 +/- 0.05) host star. Based on photometry from TESS and follow-up ground-based imaging, we measure an orbital period of 3.4373125 d and a planetary radius of 1.475 +/- 0.029 R_Jup. We use TRES spectroscopy to determine a mass for TOI-7169 b of 0.41 +/- 0.14 M_Jup. The planet is therefore inflated, with a low density of 0.159 +0.055/-0.054 g/cm^3. We also characterize the host star, showing that TOI-7169 is ancient (12.3 +/- 0.6 Gyr) and alpha-enhanced ([alpha/Fe] ~ 0.3), but with a Galactocentric orbit that is confined to the thin disk. TOI-7169 is perhaps the oldest and most metal-poor star currently known to host a transiting giant planet. Future transmission spectroscopy probing the atmosphere of TOI-7169 b may provide insight into the effect of metallicity on the physical properties of giant planets.

The eight-planet Kepler-90 system exhibits the greatest multiplicity of planets found to date. All eight planets are transiting and were discovered in photometry from the NASA Kepler primary mission. The two outermost planets, g (\\(P_g\\) = 211 d) and h (\\(P_h\\) = 332 d) exhibit significant transit-timing variations (TTVs), but were only observed 6 and 3 times respectively by Kepler. These TTVs allow for the determination of planetary masses through dynamical modeling of the pair's gravitational interactions, but the paucity of transits allows a broad range of solutions for the masses and orbital ephemerides. To determine accurate masses and orbital parameters for planets g and h, we combined 34 radial velocities (RVs) of Kepler-90, collected over a decade, with the Kepler transit data. We jointly modeled the transit times of the outer two planets and the RV time series, then used our two-planet model to predict their future times of transit. These predictions led us to recover a transit of Kepler-90 g with ground-based observatories in May 2024. We then combined the 2024 transit and several previously unpublished transit times of planets g and h with the Kepler photometry and RV data to update the masses and linear ephemerides of the planets, finding masses for g and h of \\(15.0 1.3\\, M_\\), and \\(203 16\\, M_\\) respectively from a Markov Chain Monte Carlo analysis. These results enable further insights into the architecturally rich Kepler-90 system and pave the way for atmospheric characterization with space-based facilities.

We present the eccentricity distribution of warm sub-Saturns (4-8 Re, 8-200 day periods) as derived from an analysis of transit light curves from NASA's Transiting Exoplanet Survey Satellite (TESS) mission. We use the \"photoeccentric\" effect to constrain the eccentricities of 76 planets, comprising 60 and 16 from single- and multi-transiting systems, respectively. We employ Hierarchical Bayesian Modelling to infer the eccentricity distribution of the population, testing both a Beta and Mixture Beta distribution. We identify a few highly eccentric (e ~ 0.7-0.8) warm sub-Saturns with eccentricities that appear too high to be explained by disk migration or planet-planet scattering alone, suggesting high-eccentricity migration may play a role in their formation. The majority of the population have a mean eccentricity of e = 0.103+0.047-0.045, consistent with both planet-disk and planet-planet interactions. Notably, we find that the highly eccentric sub-Saturns occur in single-transiting systems. This study presents the first evidence at the population level that the eccentricities of sub-Saturns may be sculpted by dynamical processes.

We report the confirmation and characterization of four hot Jupiter-type exoplanets initially detected by TESS: TOI-1295 b, TOI-2580 b, TOI-6016 b, and TOI-6130 b. Using observations with the high-resolution echelle spectrograph MaHPS on the 2.1m telescope at Wendelstein Observatory, together with NEID at Kitt Peak National Observatory and TRES at the Fred Lawrence Whipple Observatory, we confirmed the planetary nature of these four planet candidates. We also performed precise mass measurements. All four planets are found to be hot Jupiters with orbital periods between 2.4 and 4.0 days. The sizes of these planets range from 1.29 to 1.64 Jupiter radii, while their masses range from 0.6 to 1.5 Jupiter masses. Additionally, we investigated whether there are signs of other planets in the systems but have found none. Lastly, we compared the radii of our four objects to the results of an empirical study of radius inflation and see that all four demonstrate a good fit with the current models. These four planets belong to the first array of planets confirmed with MaHPS data, supporting the ability of the spectrograph to detect planets around fainter stars as faint as V=12.

Coat color and type are essential characteristics of domestic dog breeds. Although the genetic basis of coat color has been well characterized, relatively little is known about the genes influencing coat growth pattern, length, and curl. We performed genome-wide association studies of more than 1000 dogs from 80 domestic breeds to identify genes associated with canine fur phenotypes. Taking advantage of both inter- and intrabreed variability, we identified distinct mutations in three genes, RSPO2, FGF5, and KRT71 (encoding R-spondin-2, fibroblast growth factor-5, and keratin-71, respectively), that together account for most coat phenotypes in purebred dogs in the United States. Thus, an array of varied and seemingly complex phenotypes can be reduced to the combinatorial effects of only a few genes.

The question of how Zika virus (ZIKV) changed from a seemingly mild virus to a human pathogen capable of microcephaly and sexual transmission remains unanswered. The unexpected emergence of ZIKV's pathogenicity and capacity for sexual transmission may be due to genetic changes, and future changes in phenotype may continue to occur as the virus expands its geographic range. Alternatively, the sheer size of the 2015-16 epidemic may have brought attention to a pre-existing virulent ZIKV phenotype in a highly susceptible population. Thus, it is important to identify patterns of genetic change that may yield a better understanding of ZIKV emergence and evolution. However, because ZIKV has an RNA genome and a polymerase incapable of proofreading, it undergoes rapid mutation which makes it difficult to identify combinations of mutations associated with viral emergence. As next generation sequencing technology has allowed whole genome consensus and variant sequence data to be generated for numerous virus samples, the task of analyzing these genomes for patterns of mutation has become more complex. However, understanding which combinations of mutations spread widely and become established in new geographic regions versus those that disappear relatively quickly is essential for defining the trajectory of an ongoing epidemic. In this study, multiscale analysis of the wealth of genomic data generated over the course of the epidemic combined with in vivo laboratory data allowed trends in mutations and outbreak trajectory to be assessed. Mutations were detected throughout the genome via deep sequencing, and many variants appeared in multiple samples and in some cases become consensus. Similarly, amino acids that were previously consensus in pre-outbreak samples were detected as low frequency variants in epidemic strains. Protein structural models indicate that most of the mutations associated with the epidemic transmission occur on the exposed surface of viral proteins. At the macroscale level, consensus data was organized into large and interactive databases to allow the spread of individual mutations and combinations of mutations to be visualized and assessed for temporal and geographical patterns. Thus, the use of multiscale modeling for identifying mutations or combinations of mutations that impact epidemic transmission and phenotypic impact can aid the formation of hypotheses which can then be tested using reverse genetics.